{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Implementing a Neural Network\n",
    "In this exercise we will develop a neural network with fully-connected layers to perform classification, and test it out on the CIFAR-10 dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# A bit of setup\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from cs231n.classifiers.neural_net import TwoLayerNet\n",
    "\n",
    "from __future__ import print_function\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# for auto-reloading external modules\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def rel_error(x, y):\n",
    "    \"\"\" returns relative error \"\"\"\n",
    "    return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the class `TwoLayerNet` in the file `cs231n/classifiers/neural_net.py` to represent instances of our network. The network parameters are stored in the instance variable `self.params` where keys are string parameter names and values are numpy arrays. Below, we initialize toy data and a toy model that we will use to develop your implementation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a small net and some toy data to check your implementations.\n",
    "# Note that we set the random seed for repeatable experiments.\n",
    "\n",
    "input_size = 4\n",
    "hidden_size = 10\n",
    "num_classes = 3\n",
    "num_inputs = 5\n",
    "\n",
    "def init_toy_model():\n",
    "    np.random.seed(0)\n",
    "    return TwoLayerNet(input_size, hidden_size, num_classes, std=1e-1)\n",
    "\n",
    "def init_toy_data():\n",
    "    np.random.seed(1)\n",
    "    X = 10 * np.random.randn(num_inputs, input_size)\n",
    "    y = np.array([0, 1, 2, 2, 1])\n",
    "    return X, y\n",
    "\n",
    "net = init_toy_model()\n",
    "X, y = init_toy_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute scores\n",
    "Open the file `cs231n/classifiers/neural_net.py` and look at the method `TwoLayerNet.loss`. This function is very similar to the loss functions you have written for the SVM and Softmax exercises: It takes the data and weights and computes the class scores, the loss, and the gradients on the parameters. \n",
    "\n",
    "Implement the first part of the forward pass which uses the weights and biases to compute the scores for all inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "\n",
      "correct scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "\n",
      "Difference between your scores and correct scores:\n",
      "3.68027204961e-08\n"
     ]
    }
   ],
   "source": [
    "scores = net.loss(X)\n",
    "print('Your scores:')\n",
    "print(scores)\n",
    "print()\n",
    "print('correct scores:')\n",
    "correct_scores = np.asarray([\n",
    "  [-0.81233741, -1.27654624, -0.70335995],\n",
    "  [-0.17129677, -1.18803311, -0.47310444],\n",
    "  [-0.51590475, -1.01354314, -0.8504215 ],\n",
    "  [-0.15419291, -0.48629638, -0.52901952],\n",
    "  [-0.00618733, -0.12435261, -0.15226949]])\n",
    "print(correct_scores)\n",
    "print()\n",
    "\n",
    "# The difference should be very small. We get < 1e-7\n",
    "print('Difference between your scores and correct scores:')\n",
    "print(np.sum(np.abs(scores - correct_scores)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute loss\n",
    "In the same function, implement the second part that computes the data and regularizaion loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Difference between your loss and correct loss:\n",
      "0.0189654196061\n"
     ]
    }
   ],
   "source": [
    "loss, _ = net.loss(X, y, reg=0.05)\n",
    "correct_loss = 1.30378789133\n",
    "\n",
    "# should be very small, we get < 1e-12\n",
    "print('Difference between your loss and correct loss:')\n",
    "print(np.sum(np.abs(loss - correct_loss)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backward pass\n",
    "Implement the rest of the function. This will compute the gradient of the loss with respect to the variables `W1`, `b1`, `W2`, and `b2`. Now that you (hopefully!) have a correctly implemented forward pass, you can debug your backward pass using a numeric gradient check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W1 max relative error: 3.561318e-09\n",
      "W2 max relative error: 3.440708e-09\n",
      "b2 max relative error: 1.217781e-10\n",
      "b1 max relative error: 1.555470e-09\n"
     ]
    }
   ],
   "source": [
    "from cs231n.gradient_check import eval_numerical_gradient\n",
    "\n",
    "# Use numeric gradient checking to check your implementation of the backward pass.\n",
    "# If your implementation is correct, the difference between the numeric and\n",
    "# analytic gradients should be less than 1e-8 for each of W1, W2, b1, and b2.\n",
    "\n",
    "loss, grads = net.loss(X, y, reg=0.05)\n",
    "\n",
    "# these should all be less than 1e-8 or so\n",
    "for param_name in grads:\n",
    "    f = lambda W: net.loss(X, y, reg=0.05)[0]\n",
    "    param_grad_num = eval_numerical_gradient(f, net.params[param_name], verbose=False)\n",
    "    print('%s max relative error: %e' % (param_name, rel_error(param_grad_num, grads[param_name])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the network\n",
    "To train the network we will use stochastic gradient descent (SGD), similar to the SVM and Softmax classifiers. Look at the function `TwoLayerNet.train` and fill in the missing sections to implement the training procedure. This should be very similar to the training procedure you used for the SVM and Softmax classifiers. You will also have to implement `TwoLayerNet.predict`, as the training process periodically performs prediction to keep track of accuracy over time while the network trains.\n",
    "\n",
    "Once you have implemented the method, run the code below to train a two-layer network on toy data. You should achieve a training loss less than 0.2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final training loss:  0.0620081785931\n"
     ]
    },
    {
     "data": {
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AAMACI5BlqLokLEnqGGBiPwAAWFgEsgxNBDI6ZAAAYKERyDJUlR6y7BwgkAEAgIVFIMtQ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\nst75KFcAAAALSURBVIiIiIjC/gUS5zDbLYqCcAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd254c05bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "net = init_toy_model()\n",
    "stats = net.train(X, y, X, y,\n",
    "            learning_rate=1e-1, reg=5e-6,\n",
    "            num_iters=100, verbose=False)\n",
    "\n",
    "print('Final training loss: ', stats['loss_history'][-1])\n",
    "\n",
    "# plot the loss history\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.xlabel('iteration')\n",
    "plt.ylabel('training loss')\n",
    "plt.title('Training Loss history')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the data\n",
    "Now that you have implemented a two-layer network that passes gradient checks and works on toy data, it's time to load up our favorite CIFAR-10 data so we can use it to train a classifier on a real dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 3072)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 3072)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "from cs231n.data_utils import load_CIFAR10\n",
    "\n",
    "def get_CIFAR10_data(num_training=49000, num_validation=1000, num_test=1000):\n",
    "    \"\"\"\n",
    "    Load the CIFAR-10 dataset from disk and perform preprocessing to prepare\n",
    "    it for the two-layer neural net classifier. These are the same steps as\n",
    "    we used for the SVM, but condensed to a single function.  \n",
    "    \"\"\"\n",
    "    # Load the raw CIFAR-10 data\n",
    "    cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "    X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "        \n",
    "    # Subsample the data\n",
    "    mask = list(range(num_training, num_training + num_validation))\n",
    "    X_val = X_train[mask]\n",
    "    y_val = y_train[mask]\n",
    "    mask = list(range(num_training))\n",
    "    X_train = X_train[mask]\n",
    "    y_train = y_train[mask]\n",
    "    mask = list(range(num_test))\n",
    "    X_test = X_test[mask]\n",
    "    y_test = y_test[mask]\n",
    "\n",
    "    # Normalize the data: subtract the mean image\n",
    "    mean_image = np.mean(X_train, axis=0)\n",
    "    X_train -= mean_image\n",
    "    X_val -= mean_image\n",
    "    X_test -= mean_image\n",
    "\n",
    "    # Reshape data to rows\n",
    "    X_train = X_train.reshape(num_training, -1)\n",
    "    X_val = X_val.reshape(num_validation, -1)\n",
    "    X_test = X_test.reshape(num_test, -1)\n",
    "\n",
    "    return X_train, y_train, X_val, y_val, X_test, y_test\n",
    "\n",
    "\n",
    "# Invoke the above function to get our data.\n",
    "X_train, y_train, X_val, y_val, X_test, y_test = get_CIFAR10_data()\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train a network\n",
    "To train our network we will use SGD with momentum. In addition, we will adjust the learning rate with an exponential learning rate schedule as optimization proceeds; after each epoch, we will reduce the learning rate by multiplying it by a decay rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000\n",
      "iteration 0 / 1000: loss 2.302783\n",
      "iteration 100 / 1000: loss 2.302079\n",
      "iteration 200 / 1000: loss 2.286357\n",
      "iteration 300 / 1000: loss 2.190002\n",
      "iteration 400 / 1000: loss 2.091589\n",
      "iteration 500 / 1000: loss 2.067465\n",
      "iteration 600 / 1000: loss 2.052669\n",
      "iteration 700 / 1000: loss 1.930477\n",
      "iteration 800 / 1000: loss 2.074204\n",
      "iteration 900 / 1000: loss 2.059914\n",
      "Validation accuracy:  0.29\n"
     ]
    }
   ],
   "source": [
    "input_size = 32 * 32 * 3\n",
    "hidden_size = 50\n",
    "num_classes = 10\n",
    "net = TwoLayerNet(input_size, hidden_size, num_classes)\n",
    "\n",
    "# Train the network\n",
    "stats = net.train(X_train, y_train, X_val, y_val,\n",
    "            num_iters=1000, batch_size=200,\n",
    "            learning_rate=1e-4, learning_rate_decay=0.95,\n",
    "            reg=0.25, verbose=True)\n",
    "\n",
    "# Predict on the validation set\n",
    "val_acc = (net.predict(X_val) == y_val).mean()\n",
    "print('Validation accuracy: ', val_acc)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Debug the training\n",
    "With the default parameters we provided above, you should get a validation accuracy of about 0.29 on the validation set. This isn't very good.\n",
    "\n",
    "One strategy for getting insight into what's wrong is to plot the loss function and the accuracies on the training and validation sets during optimization.\n",
    "\n",
    "Another strategy is to visualize the weights that were learned in the first layer of the network. In most neural networks trained on visual data, the first layer weights typically show some visible structure when visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ger0lHE6cU9TJrtvjn28GACSlNbGEZnPimrPZb2V93MzZS0iO36VPLzTbwNz5\nzip8uHJvs+2BIIjWhUQcQRAtRrGHmBLI/eT6dMy3HeM8feWoXBUrh2Y3HahDYcTd5kSM9wKsdiMJ\nVbMJLzkc+sWGA67mvZrGHU6cagv7zt1YhiPv/hgVde4pFIdCfTyJ8Xd9jLv+t1rfp8PxE+/tuXlb\ncd1LS5v03gRB5A4k4giCaBHm33oSvvjNib7n5XBqr1JdxAl3LqlpCKTJiSuyiTjrWs/N24q9HgUP\nry3egQ37agBYrlxc1cy+coAeThVc9vQil7PWkFAdOXGarTr1uXlbUV4Xx3tNXIFaF9P3++yXWwG4\nJ0McqI016f0IgshNSMQRBNEi9OyQj9KCsO95WcSJxyFDualp6gMUBpvb5syfW7nLnRMH6LltgJUf\nF09yu4jTnIUOdrE0+vczXU6cbBiOMmazLnEUVQB6+5KdFf7tV1LhDPMmHc/LSMQRxGEBiTiCIHKC\nod2KMKFfKa44qr95LGyERTWNoy6u+r0UjDGbE+fs97a3OopwQMHRgzvbjhujYVEft8KpcluRhDMn\nzkNN2py4hGaOEpNf7zVK7M1lu3Dsn+xNf7UMc+jcVbT215GII4jDAxq7RRBETlBaEMZ/fnKM7Zio\ndVA5d/V5k2Gw58R5aaGRPYvx94sm4OHPNmBzWR2+2FBmiqF604nTsKWs1nyNM9fMa6C9LPRijj5x\nosGw6EknNw9euPmg61pxVUOeknqsmfOe8aTmFnE1TZuD15os3HwQkwZ0SludTBCHI+TEEQSRswQM\nq0zTOE4d1R0AcOyQLgCA44d1xblH9gEAnDq6u03EOSct6NfSW5384TtjcOsZIwFYIqs+rjtlX2w4\ngHP/Od98jTNs6XwuX0N/bA+nioIJIRJlreUlCJ1TJWav2+9yAwG7E1cfT7rCqfUJt/PXFlmw+SAu\nfGIBHp21sbW3QhA5CYk4giByFuHEJTWO+849AqvvOg15Id2pKowE8OAF4zDvlpPw1wvHo1BqK+IM\npwLAil1V5uNISL9wzOHEOUO2TieuwSOkG02oyJOuJ1fRChEnWn7I1a5eIk4WZ/M2luHKZxfjoU83\nuNbFbCJO9ayafe+btjfOK5pQce8Ha8zPeV+1XpCyfn9tqpcRxGELiTiCIHIWIYhUzhFQGArCQYSD\n+rE8I1+uV2k+IsEAgobiu/yo/hBa6bJp/fHBDcfZrgVYVa+xhApN46aIc+J0wbzWRROq2aMultDk\nXr/mfFbKf1woAAAgAElEQVSRE2fPn3NfS3b69tfoeW1bPWbPyvuqj6susalqwPWvtL1xXs9+uRWP\nz9mMp+duth33clYJgiARRxBEDiPyoOSEfyHAhJsms+XeM/GHb482nbgzxvTAyJ4lePLySbZ8O9mJ\na/AQU4KEqiE/ZDl8Iuz67A8mW/csq0OBURmrh1MlJ85oXVITTQCwu28frd7nul8soeLd5buRVDXz\nPXi1x3OGU51i08uJbAsIx1LjwKdrrM+nbb4borG8/fUuvLN8d2tvo01AhQ0EQeQsAeHESeJHjPOS\nG/oKhIASIibPCLGeYuTTCcRr40nNdNeKIkHUxuy5ZAmVI65q6NkhD3uqonh10Q4AwIgexeaastq4\n+TyW1GyCQ2ipurjeT05NM4br30t34tHZm3DrGSPQuUgfVebV5DjuCKfKQhNo3kkRALC7sgG7Kxsw\naUCnJr2uEKOz1u3HXz5ejzG99RYtpOIaB+ccCZXb2ve0BW547WsAwLfH9WrlneQ+besnSxDEYYXp\nxEnOUijo78QJhIZxihuBaAYcS2qmuzaubwfXuvp4EqrGbXNZva4rxnzFkhpUn6H3tbGkZx6czO7K\nBgB6SxSewomTnbd/fLoBGx05Y0mfPTQVJz04G+c9Nj/9wiwRuX6V9bpzuatC/zw4qbhG8cBH6zDs\n9g/M3Eyi/UEijiCInEWIOFn8iAKGQIoxXEL0hXzGPFgiTsWDH60HYDXmlalu0MVESV7Idry0IIzL\npln97ILGPmMJd36aoDaWTOuQyTlxYuVby3ZhgaMdibxu3qaDuOmN5bbzzirXpkbk+jU1Qpw6f25t\nNDrc6rxmOMdefQqJ9gGJOIIgchazElUabj+mt+6Yrd1b4/s68aXPfIQeYwzhgIJYUjNzbwo95rpu\nMBwupxMHAEdJjYM1rgvDg3VxrN1bgyP7lbrWH3PfZ2a1pR+2Jr6ScHl+3lbbunQi7VBF3JayOqxL\n8fk2F+L9i/Cf+Pk1h4jzqjRub5ifHzmZ7RYScQRB5CxHDeqMm08bjj+eM8Y8dozRJ0787cW3jugJ\nAOhc6D/mKxJUsNMI1wHA0YPd13th/jYAQLHDiQOs3DxAz0GLBBW8vHA7AKCjz3gxuc2JF7L4Wra9\nwnwcDNj/qXZObBDc+72x6FQYRuwQnbITH5iN0/72edp1TV01Kpw4Z75jU4uQN5bswMg7PsSWsrom\nvW6uIf4fhpzM9gsVNhAEkbMoCsP1Jw6xHetSFMGau043e7N5ceOMYbh6+iBXGFSmJpbEu4YL98D5\n4zC4a6Hv2gM17jFWQSnkp3GOSCgAGGErv5Yl6XKThIhZtKUcq3Zb815DjmkFXg2AAT0kXJIXRCzZ\nMi6TnjRv7W3Fzir061yADvn+n3u66wFWeFpcualFyMxVeuXrhn01GNjF/+fe1hG/Nm21WplIDzlx\nBEG0OfLDAd9QKaCLv1QCzkn/zgWe4VTBsUMtl+53Z48CYLU6AfSmwBGpArAu7p2DJIs4ucJVIBw2\np2gMOnLE/Jy4YIBBUViz58SZ+5Bz+DjHtx6eiyufXdTo64l9OyVHMxfbtlsUs1q7lTdCNBsk4giC\nOOzpUZJnE2GAVVRx3sQ+OGNMD/P4uD56Tp4cTtW4Q8TFkvjuhN6u+6zfZ1WRXn3cINd5IYoKwvZw\nYkBhuH/mWnPeqp+ICwUUBNihibhs2pPI+xAu2lfbKxt9b+EwusO0/nuKJzVU1mc7K/bwUDWKmVN4\neLzfwxEScQRBHPZ0LY64nD0REuxcGDYLLAAr6V6uoNRz4uSmwCoumtzXdR9RRDFlQCdPkSdEUZ6j\nhcmuyigembUJFz6xAIAudryMyIDCEFCY5zSIdKzfV4MBt7xnCkUAacOycljXL8SbDeIaTh2ZSoNc\n++ISjL/r40O+d3uGNFz7hUQcQRCHJcdJIVKnaAIsJ65jYdjmjFkiTips4NzWt64+ruo5cj78+MTB\n5vVlhJvlzGFKOJy1mKrZwrmCkKIgoDBfpy4VYtbq8/O3mscq6xO4573VKK/zdrrk+/i1VskGIeKE\nG2gm5qd4zax1Bw75vq1FNKE26meVKYrxK9LczZ+J1iOnRBxjrC9jbBZjbDVjbBVj7AaPNSMYY/MZ\nYzHG2K9aY58EQbR9XrxqasrzIn+tY0HIbOYLWLlwXtWpgrpY0lNkCYIeAg6wRJFTEDldrnjSW8QF\nA4YT1whhIO4oF2W8u3w3nvxiC+54e6X3flUNX22vwEOfbrDlxzWWuPG+RfhPaNnGhgPf+2YPNh+o\nTb+wlRjxuw8zqgJuLCKcmq7JNNF2aTYRxxgbzBiLGI9PYIz9nDHmbp5kJwngJs75KADTAFzPGBvl\nWFMO4OcAHmjyTRMEQRiIBqndS/JsgskvnBqWwqlJjaecKOHlwgEw57hudrS+SDi+hGujSc9CjKDC\noDDWuOpUQyjJglGIwSqj6bGTeFLDdx+dhwc/Xp92SsSHK/diwC3vocLH1RPXA6xwqirEXAbb1zyE\nyvWvLMNJD87xfU2q4pimZFdlA/72yXpPMdqcbU7Eu6PqVIt3lu/GgFve8/2dbms0pxP3JgCVMTYE\nwBMA+gJ4JdULOOd7OOfLjMc1ANYA6O1Ys59zvhhA+/gJEATRarzz02Pw4Y3HpVwzvEex7cveK5yq\nadz2BT2ub2kaJ85+7qnLJwGwBsA7cYZTK+rj6OTRAy8YUIycuMxdsXeX78Ynq61h83LoTTiCfi1T\nbDlxydRC4em5mwFYDZRfXbTddl/AysETokNV7Y5cKnLRbZr0x0/wyKyN+PFLS/G3TzZg0yG4go3J\nOVQ8Zg8f7jzx+SYAwPaD9a28k6ahOUWcxjlPAvgugIc45zcD6JnpixljAwBMALCwWXZHEMRhzxF9\nSjGihzVua2L/jq41PUrybM8jAd1xk4eKq5yb4derjx2IF6+akpETJ4RYSJrl6kWDVKhw0RPz8cma\n/Z4iLqCwrKtTf/bqV7j6hSWm25WQQrmiVYqfiJPzueJqdu7frW+twNUvLLEdqzXcT56BE/fNzkpb\ny5ZcFCpltTHcP3OdKc4ba4htKavD0N9+gLe/3pXV68T/e3h9Nl9tr8DEuz9uRGXvoRNNqPh8fevk\nMrY3U7I5RVyCMXYxgCsA/M84llHjJsZYEXQn70bOeXW69T7XuIYxtoQxtuTAgbab+EoQRMvx5o+P\nNh8/eP443DhjqCvkJsSbnNemapbQmti/I0ryQqbYkxG94YSI61YccV3LC3n25YLN5QDgKeJCAQZF\ngWd+2pKt5dh20ArdqQ73UDyUw6JCfDT49L2T79MQt99zb1UULy3Y5noN5xz7a7zHjwmxKJw4zcyN\ns3/z7qlqwLcf/hK3/9fK1Vu+s/GtTZobsfvGhm/X7dW/Bv9nFJ9kSion7uHPNuJgXRxLtla4zjU3\nf3xvNS5/ZhFWpplg0py0UCS92WlOEfcDAEcBuIdzvoUxNhDAi+lexBgLQRdwL3PO32rszTnnT3DO\nJ3HOJ3Xt2rWxlyEI4jCjZwfdeTt3Yh/cOGOY67xzricAqJpmzuLsUKD/v6qXEyeqYFVDKHU1RFy6\nCsXamDt7xDOcalSnOuGc47zH5uP4+2dj28E6aBrH2Dtn4tf//sa1Vi6qECIuEyeuwdHW5IfPLcbt\n/13pOS92yj2fel6v1rifKeI0+7nj/vwZlm6rMEXt1zss4XaR0X5FkEkxRHP2T/MSyI0VDiJ0n8wy\npGo6cTlmP4k8wMr6ls+KyrGP4pBptrFbnPPV0AsQwBjrCKCYc/6nVK9h+r+KTwNYwzn/S3PtjSAI\nwo/ZN5+Q8h96IZKK86x/PlWNI2rkoZXm6+LKKycu3xBxwrUSIs5rrJdM1CPHzWs+a1BhCCju+8pO\nzPH3z0ZeSEE0oeGNpTvN4wlDMdVKeXl1hnjzGxafSsSV1ervyflZbiv3zkWSBYqrsIHr4dMd5Q34\n84drbbN0/cgkutocEdg3l+7ElIGd0Ks03zzGfRzFTBGzc7PN+zMnNuRYqNl0CFtBUeXWJ3HoNGd1\n6mzGWAljrBOAZQCeZIylE2bHALgMwEmMsa+NP2cyxq5jjF1nXLcHY2wngF8CuJ0xtpMxVpLqogRB\nEJkSCQY8+8Y5CQUUrLjzVAC6OydETKnhxCkejthAYz6rcPNuPm04Th7RDaeP7eFam47hHmO7FIUh\n4OH2OL/8hSjs1cHK9xPFEDYRJ5w4n+bBcv6cU+iJM86Pwcv9A+whYyE6xd8c3BTFCceoLxlZrKTK\nkRMva+qqTVXjuOmN5Tj3n/NsYWlxl8YWX4jZudkWN7AcLWzIBXHpdEUf+nQDXl20vXU2cwg0mxMH\noAPnvJoxdjWAFzjnv2eMef/Xa8A5nwurKtpvzV4AfZpwnwRBEI2iOC+Em04ZhtPH9MA1Ly5FeV08\n5fD3O84ehakDO2HyAL2AomeHfDx95WTf9W/95Gh879F5ruM3zhiK00Z3tx176OIJALzbl/iJBzkk\nLIoE5BCXcOL8RIBczBB1CL1sXSdZxDnFCufWl24qIZTUOMJK5sKlqcWNOfu2Nma7tplv2MiGyIEs\n3tO/Fm/H0YO7oG+nAvPLNNdEXDbvp6V48OP1AICLp/Rr5Z1kR3PmxAUZYz0BXACrsIEgCKJd8bOT\nh2Jo92K88MMpuO97Y139244wZq0Cek7cd8b3zjjBfXDXInT2yH07bmgX1zWEe6h4XFv1EQ+yW+QM\nhwL+LU8EclsR5+udIdF0VEct8egUOxrnZsVtPKn5Cjn5/WRy3yYXcZL4tIk4w4s71DYoiTQiUNU4\nfvPmCnzr4bkApIkNKT6L1pBRphPXGuHUdpYU15xO3F0AZgL4knO+mDE2CMCGZrwfQRBEs/HiVVOw\ndk+N7/m+nQpwkeP/4pfcPgOF4SDe+monBnctyvqeIWMCgxN5Tqu8FvB24mI+7T/kXDunkwYA9Q4R\nV1Ybs43giqn+rzd7vWUoXHZVNpiPvRoHi3BvUuOmyHNeOZlhODWbNdkgnDiFMdu1xdtR0zRE9kOI\nsHQNlcU9hZvKYHe8vtpegT+8uxqvXTOtUftoKsSvaGs2IWapg36e7Civx83/Xo4bTh6GowZ3boZd\nZU9zFja8AeAN6flmAOc21/0IgiCak+OGdsVxQ7OrdO9SpBcuXDK1f6PuGVCYZ/sRecSXQOSMeeXi\nVTd4O2py13qv4ok6R57bUfd+anOD7v9wrflYduKSqmbmO2WqWz5ZvQ/FeUHURJMux4lzqxFwQtV8\nxYzsOMr5Vv/5aieGdivGmN4d7OulNY/N2YS8oIIrjxmY2YY9EE4cg7frls5J80O83XThWKcocoql\nO95ehRW7qrBub02rttiwwqmtt4fGUBdPYsHmclx+VMv31vOjOQsb+jDG/sMY22/8eZMxRrlsBEEQ\nHjx4/jjXsZCieIoyTyfOo3+doKoh/ZfOHEfz1fxQwCbyYknVJUKqpTy2qCT4Eio3XbJMw6nr99Vg\nfN9ShIOKq5UG55bITKrcJpBkMSIflx//4l/LcfZDc5FQNSyX2pLIe7vvg7W4893Vvvtbt7cGX24s\nS/ke5Mka9py47FxJJ2Kf6ebTOq8vQu5C/Akx5xVyb0nE73RbGwcmPt/W/vxkmjMn7lkA7wDoZfx5\n1zhGEARBODh3ovv/cRU/J86jB53oJRbw+IIpr8u+H5czxy3djE95fULTrKkLGQqXuriK4rwgAoy5\nnThYEzESqmYVPnD7F6rs0HkJhAc+WofvPPIl1u6tMda71+ytimJPVYPr+Gl/+xyXPLXQt1ExIDlx\nzH5t8VAu2MimMlOsTfdZpnPixMtbW4O0bk6c8XcjsgHFr5ff7OPWoDlFXFfO+bOc86Tx5zkA1HWX\nIAgiC5wjugDvcKrIifNy7srrUvehE/TvXOB7zi8kK7CJuKRmCo5Mv6jrYkkUhoMIKMzsWSfQw6lW\nTpwsZuS3K4cbPUdNbdNdOJF/5yWkpt37KY669zOc9MBsz336NSoGrJw4BmYL7QrBIO8pmx5pQhCm\nDadq8mMutRgx9tEKTlx5XdwMhQsCOZAT15hbi59ZirHILU5zbuUgY+xSxljA+HMpgIPNeD+CIIh2\nR9AoMbSLOHc4NZzCiTtYl1kOz/kebqCgJprazZPHbiU17hqdlY7aWBKFkSAU5v6C5bAKJ5KqZhMz\n9skZqUWcUxymqhbdnMZ59MIMdzK7SLNGmmVXeOFcm65PnHxPlXOrxYjUNBk4NCeuLpbMuMKTc44j\n7/4YN772te240oo5cUJQN0rEHWbh1B9Cby+yF8AeAOcBuLIZ70cQBNGm+eLXJ2LOzSfYjonvi07S\nhIawpxPnX9hQXpuZiEvV+uSq55f4ngPs1anxZHbhVM456uMqCiMB37FhwonjsIsZefktb32DxVvL\n8caSHdh4oNZ1HeeXr3DiPlq1N+0eM8Fy4uyVqOIjkMVnNi6UWJuuRYl8zaTKpdmpmu28fOtsWm5s\nO1iH0b+fiVcX7chofYVRJTvT8fkGcqDZb2NcQM104nJHxDVndeo2AN+WjzHGbgTwt+a6J0EQRFum\nbyd3OFOEKTsWWk2Evb5ERGGDV6inPEMnbki37NugCGzhVFUzHY9MqlNjRvi1MBL0FnGQnTgrnMph\nF2YLNpfj/Mfm+97HeWnhUF3z4tL0m8yAhJQTt3yHNdxdjCCTc/ay6RmXqRMni6KkplmzU42XebV9\nyUZHbT6gu5MzV+3F96emb4q72whb9+yQbzvemjlxgsbcW3xuXm53a9HSkd1ftvD9CIIg2jR1MV28\ndCqMpFxn9onz+IKpbLCHQo8f1hVjHe02RvQoxmmjsx//JZDHbunhVP2xV+7XlUcPAAD0KNHHfolR\nX4XhoGeoKqlyPDp7EwAgmlSRsOXEZf6F6nQam6tPHAPDTW8sd523945rhBOXrtmvHE7VuGu8lTib\nrgAE0B26OesP2PYpPr5Mdy5yD7uX2H93zXBqKxY2NOZHLz4LL7e7tWhpEZc775wgCKIN0BDXBY7X\n5AYZMydOcf+z7pxretm0/pjQrxSAJf7G9y09pH3O32ylPFc1JFzzT2V6l+bje0f2Nl23ekOo6jlx\n7q+JdXutJsucW58JkF1+lzN02NQiTjhlXtMvALuLuHavf+NoJ+I1ftcVyG8noXLLiXOEUTWH2PPi\nneW7ccUzi/DqYmueqBDBmYZghRPXQ5rRC1hucTohu3DzQczdkLqtS2NpzOQGNQfDqS0t4tpWUxiC\nIIhWRgyf75RGxJktRjz+VXd++QcUZoa4RAg3GGi6LyY5pPnpmn2u9iQBhSHAmCkmLCcugAO1HpW0\njq3VGqKPS8n7mSBeJzjUMVhOYsnU4c7n52/F4Nvex/6aKC56YkHG15X3Web1+RjIokh24pyVwpnk\n5m3cr+cUltVYoXihXTLVP2JsW0HYnrllhVNTv/7CJxbg0qcXZnazDBG3bMyP/rAobGCM1TDGqj3+\n1EDvF0cQBEFkiPjCzFTEeYV6vEZq/ei4gXj2ysk4ZVR3AFYVrOCTX05Peb+7zxmDW88YkXINADw6\nexNOfGA2Nuy3Cg2Cxjgx8aVYZzhrhZGgpzMUd4gjeaZrNqGt2pg9rKxpPKUj8+mafRlfG3Dv08mq\n3dUAgD2V/r3mvJDF2dJtFf7r5MIGW06cXcR5VfEu2VqOlbusPL6aqPiZWJXQYlRVpvlkSVP02I87\nxWVLwk1XsvE5cV69G1uLJhdxnPNiznmJx59iznlzzmolCIJot5QW6IUNfmLOLyeOMe8wXDCg4MQR\n3cwvpJDDiRvSrTjlfoZ3L3Ylt//u7FG+68U8T0B34hRFd+L+981u3D9zHQCge0me38sBAGcd0ROA\n5dwB2bkitVF7r7t91VEcqPF3tkRF7t3/85/kIJPpWC2vZs1ecM7x9te7bA5fVb1/qxdZFNmrU+1F\nJrKzt6O8AT94dhHOe2w+zn5ornlcCOWiiPW1zbJ04swCFMd6EY5s3cKG7F9jFjbkkIgjUUUQBNEG\nEOLthGFWz/TLpvXHiwu2AbDylZxfMJGg4sqJk2OQIofOK5cuFcEAQ3FeCP+6ZhouNEKDmebVBY1J\nFAmV46evfAUAOHZIFwzvkVo4luTpX1nCJdKrUzPfsyz+AOCNpTsxN80oLQB4eu4W23NN454OYDyZ\nOmdNkGl14+x1B3DDa1+jWBJS0RT3sDtxVk6cUyzpuV36yb9+st7zWsIdLfAQcZmKLyFqnQUMisMh\nbA0a48TlytgyGRJxBEEQOcZNpwxz5T6N6FGCV380DUf2t4TS3eeMwa9PH469VVZ4zvkFEwkGTCeO\neTTSDZjiT3++4NaTfQfMy4hCCjlpPZxhK/uAokBhzDabdfKATmlfJ1wh4RJtO1if0f0EXk7Znqrs\nQpuALkoUj2y8TJ04pzPKOffs0SdETo0kPmVBvvlALbaU1eHkkXpIXNZE0YSK/dUx23XMGa4Z7NMU\nyramcmK/aV9u3FfzXC8EcFPnJGaDfOtMBZ1o1UJOHEEQBOHLz04e6joWDio4anBn1/HivBCK86we\ncs6ecJGggv1GyPD6E4bg4VkbMa6PJQSFdhD5Ts5KQj9EIURQEm6ZFkcEFeb6Ijx2qPu9ORHvsy6W\negRYc6NqHCH30Iy0A+oFNY6wrqpxz8+uIOy+iSwAT3pwDgBg631nmdcR3PT6cqzbZ58RazYdzkA8\nic9Y1fS5tRrn5usynTtqOnGO+wWaOSdOL+rwbl5tFTZY985YlB5mY7cIgiCIFuYbKTkdsE93OGZI\nF2y97yxbXl2qUUw/OWEwvjXOux5NFFLISd6hjJ04S8SdNro7vvrdKZjYP3Mn7tO1+zO6T1Pg5dJM\nuOtjz7XpqlMF1Y6+fX6iyksURhP+95BFkRBwgFUYkc0otFpJxB1//yyMumOmKWIy1V5mmxmf+zWH\nE5dUNQy+7X386cN1KdfZ2qxkqOLMPnE5FE4lEUcQBJHDTBuUXtzIXGoUG3Qp0oWaLOKcxQuA5ap4\nuRa/Pn0EHrp4Ak4b3d11LmTm0lmvyzScGlSY+UWYFwqgY5rKW0FRXssHj+qc+YTQ3TAvcZduooLA\n6cT5iSpneDYcUDwrjQV+WsQpvjIRT0IsqhrHPhGWNfazdFsF1u9z97lLqJrtcxFheWc/OPEs2QzD\nU8XP6+WF21Kukz+rTB3BXCxsIBFHEASRw7z6o2nY9H9nZrz+/El9sfW+s5BnxPtCUsGC15eP+P5K\n9bX0+GWTXMdCQea6fqbhVN2J0x+nE36y8JQT/FsKv7mzziIJwLvFiNf7q45m5sQ5RWFhJICGuIpH\nZm3E43M2Wa831vk5Sn/7ZIMhpER4M714Eu9F3pv8+K537RW70YSKob/9wKw01vfl7fx5tTppKmKG\nyM3zincDpoKU95RpoYZKhQ0EQRBENjDGcCh9eGVh5Rnu5MKJy/K6wokTuXEKyzicGgwwMy9Kdgq9\nCAcUJFTVeF3L+w4Ltxz0PH6gJmbLRQS8RVwkqLjCoi4nzhAz0YSKx+dsxrXHD0JeKOC6XmEkiP99\ns9vlDsZVDcGAklIUVdTHTcG+tyqGT3x64HHOcdt/VmJvtV7wcft/V1r7lMSO838I6o09vbJoO359\nut4/UIi+pMpxsDYGxhjeX7HHFFKZFoJkg3AQIz6/V+KOjXHiNHLiCIIgiJbAq6eX33B5wCpsyJSw\nIydufN/S7KpTzf50qV8jt/IY3r3Y7BUnM2Vg+pCzuIzot5cpH632FjtLtlZgzvoDtmPCOfvlKcPM\nYyEPMeEUcULsvLN8N/76yXr89WO97YdT/BWGg6aAk8WvEHupqixVjZsi7E8frvVdF01oeHXRds9z\nshPnFZoHdEdX1TjqYklz/adr92PiHz/B5c8sxO3/XWk2fvZyBBvT+kO87r4P1uKbXZUAUjhxBnYn\nLrN70NgtgiAIokWRv6w8c+KM09l+L4lwal4ogNeumYanr5ycXXWqT187J3LoKj8cwCPfP9J8/r0J\nvQFklosnXLNBXQrTrpXX7Kv2bkHy6ze/wRXPLLIdiyc19OmYj59L1cVe768m6p4cAVh5jAu2lJvX\nEygMyJOqVeVz4nEqRymW1NLOKgVSz2eVRZdzwod879v/uwKjfz8TCYeTuHKXPrHCHP/lsZ/G9v8t\nq43jsTmbzL6DTidu04Fa3PXuaqm4wzqXyecir8ulcCqJOIIgiHZIl6IIAHvBglfxgnaI4VQAmDao\nMzrkh3xdtfMn9rE9FxMbxONUyKeFWLv7nDH4zvheKMnXhVm6kCwAFBtFEcGAgqW3z0i5Vr6ec8pD\nKuKq5nIovd5eRb13Tpz4+azZo4sdOScuoDDk+0x6EFWxqaos46rmKZCcP/fUIs56HHAIdlV6D/9a\nvCPltcRnk/QIpzY2wOp08JxO3FXPLcYzX27BjvJ613r5c0sl6KiwgSAIgmgRHr90Iu757hj0KImY\nx1yTGyCFU7NUcV6unl+IzSmy5LYkzi/EGSPtlbDyeeH0XTatP/5+0QRzfFUmTpxoTxIKMHQuiuCr\n352Cf193lOda+bOoTiPixv5+JuZuKMOd76xCPKmZ79UUqR6f6wFHI2dnM17hrMkiTmHMN0QYM8Op\n/vtMqJqnQHK+xut3xNqntZ+Q4+fmFJwAUB/3/uzE+014hFMbM4orllQx5f8+tR3Lcwhe8ZkKF83P\niUslhIXmzHTiRktAIo4gCKId0q0kD5dM7Q/Z7OjTMd+1rrFOnJfo8xOCLhEnJeE7vxCfusJeCStf\n0+n0CfHmlXfmpMQIpwoHsWNh2HQrncj6xFlJ6qQmlsSlTy/Ec/O2IiaJOPG+vMZzlTnmte4or8f+\nmiicHTfkkCljQL6PiMsknBpPahkJpMp672pc/frWY+eYNtOJgyWU6n0EoXAevSZuZKrhNh+oNe9Z\n5lFBHAnaPyvx0Xj1ypOFW6rP0Ayn5pByyqGtEARBEE2N+OJ57NKJKC3w6MdmthhpGndh631n4Zgh\n9nhQrQ4AACAASURBVOkLXk5cMsPQlHza6fQJEScfvv7EwZ7XET3mZBfQayKCfk9rjVfFqR/V0YQp\nNMX78tK1Bxwi7vtPLcSUez7FSwus3mbxpIa4pMA1zT9sfKA2BlXjqcOpSc1XVMnsqmzwPWdz4hw/\nC3lUWzoRJ1y7FTurEHPMgl2yrTztHreU1eGkB+eYBSBev0JOJ86ZC6f5CLdUQlf8zjrzAVuT3NkJ\nQRAE0eSIL6WITz6V+MpqyjQfp/CJOBy0gMJMcRnMorDB6fQJUSMfP3lkdzz8/Qmu64hwqlx8kecn\n4hr5YZTXxU1hOaJHsX4tDxXnN55LrnatqI/bPseEpvmG8a54ZhH+/OHalJWdzjw8P0TOmBdyIYKz\niMXK60sfThW5cHFVw+5Ke+HI959cmHaPQgSL9i9en7HbiXM0HObAH/+3Gi8v3JZxuxFxjRzScCTi\nCIIg2jPiS8mvb5Ymffmm4r2fH4unLnc3/fUi7pw0kMqJS1PRmiq8Jq5rExcK83RKCiNWYYOgwCc8\n2Vg9u+1gvbmnp66YhBd+OMUUj9mypawOZVLuHOepxeWby3ZhT5V3JS0A7K3yd9hkdpSncuLkz9n+\nGctFCmKb9TEfJ07OQcug8bATcX0vV03gduLs5zk4npq7Bb/9z0rb+7rj7VW+UzH8UgBaExJxBEEQ\n7RjxBedXOZppn7jRvTpgxqju+NO5Y3HOeO95qgKXE+dwRQIKM7+8030hphoqb4o4RwFAOOi+Zr45\nwUIulPD+TA7FlRTOYmlBGNOHdW10y4yLnliAfy/daTuWqi1LWW0Mv/3PStdxwe4UAk9mZ6W/E5fK\npZKFtBCb9T5iSP55NWZ+KjOLE6xmwk6cv+/OvcvaUQ5D/+erXXhzmf1zd16DqlMJgiCIFkF88fh9\n7/TvXAAA6O1R9ODFhZP74W8XucOVMs5xUU4nriQ/lHFOXKqcNBG6lDv/BwPekyOEM5PJVIl+nQrS\nrvHDKTr9JModZ4/C3y8an9W1hTgq9AkDp+KfszelPH/H2aOQF1Jc+XqCoMJsYifpcNAsYWb1APQT\nfbLo8hJgTgbc8h4Wb7Vy5UwnTnMXKfjhbB0i/4469+m3b41zMJZ9JXdzQiKOIAiiHSO+I/0alF46\ntT9eumoqzhjTo8nu6RRxvUotgXjrGSPQpSiScU5cJk6cHJILMO9wqnj/3Uvy0uweOG5oVzx4/jjz\nuV/rFC9iCYeI8xEYUwd1Qo8M9iIjPqqOhR4FKodAj5I8/PDYgSjND3tWegK6W6U6xNeO8nos3Kzn\npcmOWjqRI/9+ZNpS5JWF1hQJZ5sQL9HlN69VcLDOep/7q72FqxNV4zkVSgVIxBEEQbRrhIjwc7wU\nheHYoV2a1F1wumenjOqOBbeejI33nIFrj9erR5vCiYt45MQFFO9w6v4aPZzYs9RfOJm5XAkVxw3t\nYh5PN8JJJppMXwEKAF2LIxk1KZYRn5Vfa5R0dPYRfwEzBBxCuSFuPrjhONt6zoEHjWpQQHc/T3xg\nNi58YgEAy1HTCxtS70PuD5dpOLU2ZhVJiF9VIcy8RZz9ubNy9/6Z68zHFY62Kn6/kSrnjS56aS5y\nSsQxxvoyxmYxxlYzxlYxxm7wWMMYY/9gjG1kjH3DGDvS61oEQRAEcOm0/gAOLUSYLR3y3fNJe3TI\ns+WgWflFjf8asnLi7An3XiHTvYbb0rODt4i76ZRhuPyoAQCAhngSEUm4+bUi8cIvKd5JfiiQUWhX\nRjhQjXWDrj5ukOdxUWkqv89QQEkpsJOaZhNgSYcbmgr555Xp8HmvSlfxWq/WKrIDuquyAdGE//8M\nOJ1jvyofLQeduMaVzTQfSQA3cc6XMcaKASxljH3MOV8trTkDwFDjz1QA/zT+JgiCIBxcMKkvLpjU\nt0Xv+cyVk/HZ2v24/b/+ifaWiEt/vZk3TjcdIplwIGC7FqC3f/AKp944Yyh2VtRj8oBOtuOLfnsy\nQoqCjoVhvL5EHxfVvSTPVs3r12TXC6dY8IsW5ocCvhXDfggRpyjA+z8/Dmv2VOOmN5Zn/PrCiPf7\nEGJNFm2hALP1upPfx+CuhTYhxjm3nDikb9GSaISIqzMqXROqhrv/t9q4r37OK69OTtn7xb++Tnnt\nTHsBqlpuFTUAOebEcc73cM6XGY9rAKwB0Nux7DsAXuA6CwCUMsZ6tvBWCYIgCB96leabDqAfwkXL\nJFQ5vEcxjhrc2XVc5KolHYPZvcKpR/briM9uOgHFeXaXsFtxnpljdv7EPnj1R9Pw7XG9bAIrkz2e\nOkofF5apExcMeDuGTjoW6PstDAdMwaswhlG9SnCuYyatF/JIsoKwt2+z+UCdeV1BKKCYz/Mc1cVB\nRbF95gmVu0LaqZBfq2ocnHOs3Vud8jXCift0zT4s3loBwHv6gkA+lk52OfMuxfqGuIo73l6JGmNq\nh8Z5k/ZTbApySsTJMMYGAJgAwNn5rzeAHdLznXALPYIgCCKH+c0ZI/DTE4fgrLHu/wefc/MJ+PN5\nRwAApg/r6nsNrz5xipJZBaoXjDEcNbgzGGO2HMFMRNyoXiUA3CKOpxjpLufEXTqtn+eaI/qU4vHL\nJmLWr06w5rFmoSTkprzpqlrltfJjZ6PoYIDZ3K9oUrW7oVmEU5Maxwvzt+H0v32BeZvKfF/TYHyu\nci+8THPi/ELoAqcTJ6738sJteGH+Njw8a6N5PNecuFwLpwIAGGNFAN4EcCPnPLU897/GNQCuAYB+\n/bz/4yAIgiBah5K8EH512nDPc/07F6JPxwJU1sdx0RT/f7+FWHPmxAUDjWzO5kMmYU9RaXriiG62\n46mKL2WxWejTFDgUUHDaaL1yWIijbIpQ5JUFaRoP25w4RbGmfXjMvpUb9kYTqmPsVuo92dt7aFi1\nuwoAsGFfre9rxGe1r9reAFm/hndO3P7qKBZuKUe3NFXATicuntSgahyvLNIrYsXvl8pzT8TlnBPH\nGAtBF3Avc87f8liyC4Cc4NHHOGaDc/4E53wS53xS167+/ydHEARB5B4BheGa6YPNwfVeBD3CqQGF\nZdUSJBMiGThxpQVhzLvlJNNBzAQ51FnkE+qUTUWRVC/riHAa11GWN7IT17U4gjPH2tvKyO1eQkFL\nxDmdyJDCsKvCagocS2i26tS0TpxtYoPlLKYKRYsr7q/O1InjuPjJBfjZq1+hLuY9/mtcnw4AgETS\n/vq4quGlBdvMMLMQi5rG0763lianRBzT//fiaQBrOOd/8Vn2DoDLjSrVaQCqOOd7WmyTBEEQRE4g\nChic+VihJh5umU4oAXrRQK/SfNd0ilSeoBxO9XPi5CINM5wqCYlPbzo+ZeWx7AQWhIPoXqK3J3n1\nR1Nxx9mjbWtllymoMPO1rpy4AMMmQ+AAbicunVul2kScZjqLqSpINx2ow3NfbkGZVOBi9onzsDsP\n1sXNPe6viXnuSfys4qpdPMaSmn3kGSyxSE5cao4BcBmAkxhjXxt/zmSMXccYu85Y8z6AzQA2AngS\nwE9aaa8EQRBECgIKw1XHDmy26wvnyB5OZQhlWfWZDjmc6Jej51c0kGoovewYlni0ZQHslZ7ioWwG\n9e1UYBZVeN5fkpEF4QBOHaW7b+FAAEV59j07CxuESHLlxDlEcjRhtRthYFmFe5OaVSwQS9Nj7853\nV+OrbRXm81RO3BcbrPy6/dVRzzYx4n05c+L+vWSHLcQqh21zTcTlVE4c53wu0hSScP2/iOtbZkcE\nQRBEY9n0f2c26/VFOFV1OHFNHfHqWpy+ua5f+45UTpzcN09UoTqRI8PCgXPqwlRNgznXewRuL69H\nXiiA339rFM6b2Af9Ohe4RlGJz1Nhwk3zy4mzf8DRpGoT0s7rpmL93hq8tEDPPUvlxAlqpNBoqpw4\nmf01MeSHAqiNJW2fnXBYnSJud1UUL8zbZj5/bt5WXHXsQMqJIwiCIIimomOB3hpEbrURYE0fTu2T\nwVzZQh8nTpDuu7+0wHuags2J87lIShEH4OWrp+LGGUPRvSSCYEDBuL6lntcTTpwQl6YT59FiREYP\np1o5cQkts75rAPCPzzZa18lw2oUglRMns78mhpBHSxfTifMY7dbgyM97/PNNNHaLIAiCIJqKwkgQ\n6/54On4xY6jpkCgKa/LRSOmqG4EUUx0MfZHOwSnyzYmTw6nZizhwPeR644xhacOcYo9hU8SJwgb7\n9Z2FI9GEhmSKgfKZkmmPPUGmIk7VOEIB5sptNHPikun3m1S53ieOnDiCIAiCaBoiwQAYY3jv58fi\n9rNG2s75zQrNlky+t/0KEwRCIB0/rCsev2yix/nUr5PXOCVHqsKLVH3q/O4lwqXczIkLmPf55JfT\nbWFgQBdfX++oBKDnQ3lNUMiEmCOsme5zF7rRq9kvAJTkBc33FAoorjCwCBO7xm55kNT0qRS55sTl\nVE4cQRAEQTSGET1KMKJHifl85o3TEQkqOOGB2Y2+5hOXTURlfQIsTc//gMJ8e8kJeSFctJ+fPBQT\n+3f0uIb362X3zc+JS9XHLlWfOgD47KbjzaIMIVBE2LGqQZ9UUGCIuN4d8zGkW7HNHQT0AfIfrNxr\nPk9mEU6ViTmcuKCieIY6BaJoJOnjxIWDCjiAmmgSwYDiCgOLzy1dQQWgu3kJVUvterYCubUbgiAI\ngmgChvcoRqeiQ3PiTh3dAxdM7msrlPCSUUO6FvmGKoXQEGedAkjg5/CcONxqHuwn4lJNqPBzqQSD\nuhahhzHRQDhVIWOPxw3tAgDmyDPhajnDq5X1CfPx7qqorSFvNjgLG9KFoNOFU4OKYs69DQWY67MX\nDqO470WT/WcMJzWOeA6KOHLiCIIgiHZJJv3dMkH+6r9sWn/MWX/AfD6oayFm/mK672uFvGBmo14f\nEefRoPj33xqFGVL7ED9Rk66wIVOchQ2PXzYRqsYxf9NB/bhxf2f+nnDsDhVnTlwwwIAUlxbazU+o\nBgPMdN9CAcX1+YnfD1HEcP2JQ1BWG8c3Oyuxv8YuRJOqhkSSN3kj6UMltyQlQRAEQTQRfq5Xtgjd\nddro7jZRlQlCX/jtJBxQMKJHsacTV+yYVpFpdap8qXThVBkrf0z/uyAcRHFeyDweMEWcfV+yE3co\nOHPi0v38RCsTvxy8UEAxp00EFeabEyfuGwwwPHXFJDz7g8muayVUjpiqIRxMP72jJSEnjiAIgmiX\nNHVPLy9BdKh3WHP36QCAcmkSgcDp+oi342wg7HQcrQ5v2SEXAdjuq9gdOmdPvMp6994bg9OJ88sT\nFAgHzunEhYMK4kkNQYWZVcPhoOISyqLFiMjFE++7OOLu2adqGhJJDWFy4giCIAii+clmckAqpg7s\njOK8IK47YTAA4MnLJ+HCSXr+1NRBnVO+9trjBwHwbxgcUJj5x4lTnPnlzQknblj3Imy976yU+0mF\ns7DBeVw4Y8WOSQ+VTRVOTToLG9LlxOl/Owsb8ozPIxhQkB+2nDjnZyxajIhwqugv6Hx/4h6UE0cQ\nBEEQbYyOhWGsuPM08/kpo7rjlFHd8aPpg1LOLQWAS6b2xyVT++Psh75Iuc5LxDlbefiGU411je3P\n5tyDM+zoDKc626lk4sQxlj606yxscO7DienEOUVcKIDqaBKhAEN+SN+rV06cCKcKB1DczzmODLCq\nU1MVkbQGubUbgiAIgmhiepemn7jQGIZ0K8rYmenfuRAATGfIibeI856o4ETswcy/a6QDaYZTHWFM\ncV3hjOUFneFU3Yn79enDfa+dSZGJM5x6wST/alHAEq1O8SrnwYlwqmefuJAQcZq5Rv5bJqlyxJNa\nkxXLNBXkxBEEQRDtlg9vPA7ditNPXGhu/nTuEfjOuF4Y0q3I87xXqNQplnyb/QbtExYaiynigva9\niDFawhkMOYSrCKeO7tUBnQvDOOiR3xcOKK7CBScNcUvE/encschPM8pMhFFd4dSQFE6VWow4c+zC\nAUc4NYXzl9Q03YmjcCpBEARBtAxyA+DWpCgSxKmje/ie93LinK5dOidOdfSkyxa/wgbVqP4Mmk6d\n/Q7CCQspzCUkbz9rJPZVRzFn/QHU7KtNeX9ZjGk8s0kZ+lpvJy4UYFZOXEBxfS4inBpPaggoLKWD\nmdQ4YjnoxOXWbgiCIAjiMMRTxIUyFHFi1qlhdDXWj3MWMAjEBAaxR9Ec2EkoqMCZljeyZwl+e9ao\nrPeice77fmU453AOdRAOZlCxChtCAebrYIrzqYgnNZrYQBAEQRCEGy/XySnihIhyRk2Fc3ao4VTF\nUcAgEA6ZEHeDuhbh7xeNd70+qDBXkUHQZ8/p4Bk6cQ9+tB67Kuttx0SuW1Bh5siw/2fvvuPrrOv+\nj78+SdOmO0ln2jQddO+W0BbKni2rgMqqoDcoggJOBBzIrT+1t7d6i7cIN4KKWgQFREQBkS3QvRdQ\n2mZ0pStpOtJmfH5/XNdJTtMkPWlzcjLez8eDR8651vle5wrtu99Zm5TkpKrPqNkP8LuzxhzxvuhA\nmfrEiYiIyNFqa8qLtTm1Zog73ubUdnWEuMiqB907Vs+fNmtifw4ermBL0UF+/tr6qnLUDJKRwQQN\njZc158Kryy9eX3/UtuqVJ4yRmUFz+ofb9x2VJNslW1XNYc2Rv5+cOpD7/rq66n1hSSmVXv8SZ4nQ\nvEojIiIiQG0hrvbjIpVI9awVH5PqqUSOjAYXjO7DVy8YzjcvGXXE9munZHPa0J5V74MQd+Q1ay46\nH6tKb/j9PH3rqdx57tCq76ldchLnj+rNTdMH85ULhx91fHRYrbl0WM1QF7mv5tacqpo4ERGRZqiu\n5tSaOoejOM8d2euEPi+pjj5xyUnGHecNq/WcEX26Vr1OSbaqwRXR50L1iNFYVbofXauXZEeNRI3+\nnJxBGeQMyuDm3y4MyhMOVrjvsqBPXs0zj2dZtua2dqpCnIiISDNUM7RFQlbNMNK5QzvevedcenYJ\nVoU43oUqIk2fDVmuLHp1g5TkpKOaQSPNjw/NPpk/Ly7g/FG9ufwX7xzzupV+dB+/gT068dGO/bUe\nH11mq2pOrT84Hs+ybB2aWU1c8yqNiIiI1K6ezNEvreMJN/XVVRNXn+igFN3HLCISlAZkdOIrFwxn\nUM/OMV03GHV65MXG9OvOK18+s9bjo+fZi7ysWWtWs5vd8TT1qk+ciIiINFi8G/IiGaeu5b2OpbaB\nDTWDVM1RoHWpjApxkSBoBsOimm+jRdeqVfWJq7nyBLU39caiR+f2QPPrE9e8SiMiIiL1OtbITTvO\nuFcRjiQ4nr5iEAS0mkWrGZSi38+797w6rxXdnFrbahY1HRnial8DtqaG3Oe5I3sDsG1vacznNAWF\nOBERkVYkK/341ootr1Hz1VA1l+uCo2vDooNTXZMGQ6QmLngdSx+/6Bq/SIir2fRZM2DWNUiiNp8/\nZyid2ydzzojeMZ/TFBTiREREWpE/3jKNX86e3ODzKmpM6ttQ0YEtErxq1obF2lQ7aUB61UjXSCir\n78wjBzZEylP7GV88bxhnDOvJgIzYw+7gnp1Z/d0ZjMpsHsu4RWh0qoiISDPyzj3nHrXyAdQ+IXBt\n+nRL5eJxmdw9YyTTh/aI+XMjoanmPHGxSkk2xmd1Z0VBMSnJSRwurzyuQLj8OxfSvWMKH2wvCcsT\n6RNX97WODJC1j06N1MRNHpjOly8I5o37ygXD+ekrHzS4jM2FauJERESakf5pHRmQ0emEr3Pb2Scx\nPist5uMjC90f7wBMM+P3N03lr1+YXlVrdqxpPmoTWRmiW8egnqlnl/bHPCe6OTXSl659HX3iUqKC\n5Z11zH8X7cefmHDMYxJFNXEiIiIS1Sfu+Ot3undKYUKn6uB4rEEJf/n8aVz5y3cBeO/ec49oFp01\noT9l5Y7j3P3MyqOaU3/z6VP4zbubeOuDHUeExbLyoDNdh3ZHTpYcqdtsaJ+/j5+c1aDjm5Jq4kRE\nRFqAeE8xcrx94i6b0O+obddPzQaOvcLBpOz0qteZ3TvSu2v1YIekJOPqUwbUOZ/bOSN7V039EV3m\nSBitOR1IZFRvbbWDY/o1r75usVJNnIiIiBz36NQHrpnIT68+ssnx25eM5u4ZI4+rObWm+saQpoZL\nk0UPoCgLh7XWNadbzZD64fdnVg2eaGkU4kRERISRfYOJdIfXMaFuXZKSjCSOHoWampRcxxkNM6hH\n0D9wfFZ3AH7yiQms3boXqF4GK7q2rrwi0ieujhBXcwLiZrYKQ0MoxImIiLQgx5jr97jNmtiPUZnd\nGNG3YSGuoc4b2ZspgzNiPj5nUAavfPlMhvbuAsDHovqoRWrbUmqpieuQUns4a6m1brVRiBMRERHM\nLO4BDuCxT5/S4HPqWm4rUtsWXRNXVll7TVy8wm8iNasQZ2a/Bi4FCt19bC3704FfAycBpcBN7r6q\naUspIiLS+Jbfd2G9oxci/b/SOqU0UYmav0hTaPTYh/Jj9IlrRRVxzW506m+BGfXs/wawzN3HAzcC\nDzRFoUREROKte6eUqjnSanPKoHTuv2w0379yXBOWqnmLBLXoWraqPnE1R6fWO0SiZWpWIc7d3wJ2\n13PIaOC18Nh1wCAz69MUZRMREUkkM+PT0wfXG/TamkhfuMqoFFfVJ67mPHHhIRb3yVqaTrMKcTFY\nDlwFYGZTgIFA852FT0REROImMjo1epWyssrKI/ZFRJbaykqPfc3U5q6lhbg5QJqZLQPuAJYCFbUd\naGa3mNkiM1u0Y8eOpiyjiIiINIFInziPqomrqzn14nGZbJpzCZ07NKvhACekRd2Ju+8F/gPAghVu\nNwIb6jj2EeARgJycnNbXEC4iItLG1dYnrmqy3xY8/1usWlSIM7M04IC7HwY+A7wVBjsRERFpoQaG\nE/o2VPuq5tTqFHe4vP554mK1/DsX1r9cRDPQrEKcmf0ROBvoaWYFwHeAFAB3fxgYBTxuZg6sBm5O\nUFFFRESkEaz73ozjnoA30pwa3SeuvI554hqqJQwgaVYhzt2vO8b+94DhTVQcERERibPI/HfHo7o5\n9dh94lqj1n+HIiIi0iq1r6UmLjI6VSFOREREpJmqqomL6rw2vHewRJcGNoiIiIg0U1U1cZXV2574\n7FTe316Ctab1teqgECciIiItUvXAhuqauB5dOnBalw6JKlKTav11jSIiItIqRRa+92Y+FUi8KMSJ\niIhIixSZmqQ1Lm4fC4U4ERERaZEivd4q22aGU4gTERGRlqlbOCHv+P7dE1ySxNDABhEREWmR+nRL\n5fnbpzO8T9dEFyUhFOJERESkxRqflZboIiSMmlNFREREWiCFOBEREZEWSCFOREREpAVSiBMRERFp\ngRTiRERERFoghTgRERGRFkghTkRERKQFMm8Dq8aa2Q4gN84f0xPYGefPkIbTc2l+9EyaJz2X5knP\npflpimcy0N17HeugNhHimoKZLXL3nESXQ46k59L86Jk0T3ouzZOeS/PTnJ6JmlNFREREWiCFOBER\nEZEWSCGu8TyS6AJIrfRcmh89k+ZJz6V50nNpfprNM1GfOBEREZEWSDVxIiIiIi2QQlwjMLMZZva+\nma03s3sSXZ62wswGmNnrZrbGzFab2RfD7Rlm9oqZfRj+TI86597wOb1vZhclrvStm5klm9lSM3sh\nfK9nkmBmlmZmT5vZOjNba2an6rkknpl9Ofzza5WZ/dHMUvVcmpaZ/drMCs1sVdS2Bj8DMzvZzFaG\n+35uZhbvsivEnSAzSwYeBGYCo4HrzGx0YkvVZpQDX3X30cA04Avhd38P8Kq7DwNeDd8T7rsWGAPM\nAH4ZPj9pfF8E1ka91zNJvAeAl9x9JDCB4PnouSSQmfUH7gRy3H0skEzwveu5NK3fEnyf0Y7nGTwE\nfBYYFv5X85qNTiHuxE0B1rv7Bnc/DDwJzEpwmdoEd9/q7kvC1yUEfyn1J/j+Hw8Pexy4Inw9C3jS\n3Q+5+0ZgPcHzk0ZkZlnAJcCjUZv1TBLIzLoDZwKPAbj7YXcvQs+lOWgHdDSzdkAnYAt6Lk3K3d8C\ndtfY3KBnYGaZQDd3n+fBYIPfRZ0TNwpxJ64/kB/1viDcJk3IzAYBk4D5QB933xru2gb0CV/rWTWN\nnwFfByqjtumZJNZgYAfwm7CZ+1Ez64yeS0K5+2bgx0AesBUodvd/oufSHDT0GfQPX9fcHlcKcdLi\nmVkX4BngS+6+N3pf+C8iDcFuImZ2KVDo7ovrOkbPJCHaAZOBh9x9ErCfsHkoQs+l6YX9rGYRhOx+\nQGcz+2T0MXouidecn4FC3InbDAyIep8VbpMmYGYpBAFurrs/G27eHlZtE/4sDLfrWcXfdOByM9tE\n0LXgXDP7A3omiVYAFLj7/PD90wShTs8lsc4HNrr7DncvA54FTkPPpTlo6DPYHL6uuT2uFOJO3EJg\nmJkNNrP2BB0en09wmdqEcOTPY8Bad/9p1K7ngU+Frz8F/DVq+7Vm1sHMBhN0PF3QVOVtC9z9XnfP\ncvdBBP8vvObun0TPJKHcfRuQb2Yjwk3nAWvQc0m0PGCamXUK/zw7j6Bvr55L4jXoGYRNr3vNbFr4\nLG+MOidu2sX7A1o7dy83s9uBlwlGFv3a3VcnuFhtxXTgBmClmS0Lt30DmAP8ycxuBnKBqwHcfbWZ\n/YngL69y4AvuXtH0xW6T9EwS7w5gbviPzQ3AfxD8Q17PJUHcfb6ZPQ0sIfielxKsBtAFPZcmY2Z/\nBM4GeppZAfAdju/PrM8TjHTtCLwY/hffsmvFBhEREZGWR82pIiIiIi2QQpyIiIhIC6QQJyIiItIC\nKcSJiIiItEAKcSIiIiItkEKciLQZZrYv/DnIzK5v5Gt/o8b7dxvz+iIiNSnEiUhbNAhoUIgLFyiv\nzxEhzt1Pa2CZREQaRCFOpI0xs/vDpbDidf3VZnZ2+NrM7DdmtsfMFpjZGWb2fhw+M9vM9plZcoyn\nzAHOMLNlZvZlM0s2s/82s4VmtsLMPhde92wze9vMnieY3BMze87MFof3eUu4bQ7QMbze3HBbDous\n0gAAIABJREFUpNbPwmuvMrOVZnZN1LXfMLOnzWydmc0NZ3pPCDPbZGbn17EvLs9NRE6MVmwQaYXC\npsKvACOBEmAZ8H13/3e8P9vdx0S9PR24AMhy9/3hthFHn9Uw4dqsn3H3f4WfmUcwy32s7gG+5u6X\nhte7BSh291PMrAPwjpn9Mzx2MjDW3TeG729y991m1hFYaGbPuPs9Zna7u0+s5bOuAiYCE4Ce4Tlv\nhfsmAWOALcA7BKuQxP0ZNZS7v00Mz83M7geGhkutiUicqSZOpJUxs68APwN+APQBsoEHgcsTUJyB\nwKaoANdcXQjcGC7fNh/oQbAmIgTrIm6MOvZOM1sOzCNYCHsY9Tsd+KO7V7j7duBN4JSoaxe4eyVB\n0B4UfWIMTbitSlu7X5ETpRAn0oqYWXfguwTr+T3r7vvdvczdX3D3r9dxzp/NbJuZFZvZW2Y2Jmrf\nxWa2xsxKzGyzmX0t3N7TzF4wsyIz2x02OSaF+zaZ2fnhmoOPAqeGTZ3/GTYhFkRdf4CZPWtmO8xs\nl5n9Itx+kpm9Fm7bGTY1poX7fk8QTP8WXvfr4UAFj4QAM+tnZs+HZVtvZp+N+sz7CdZGnBje12og\nHbjD3SeG/w1290hN3CAzyzezvWGT4lXAqe4+gWCty5vN7COgc9jMOiA8L8nMXgFuA/4nauDDacDs\n8PWhqO+kAmgXfn93m9kKYL+ZtTOze8zso7C8a8zsyhrP8LNmtjZq/2Qzu8vMnqlx3M/N7IHaf3sg\n/E5WhL8LT5lZanhezed2d/j7UGJm75vZeWY2g6Bf4DXhc1key7MIm5P/YGZ7gXvM7ICZ9Yg6ZnL4\n+5FST7lF2iSFOJHW5VQgFfhLA855kaA2qTfBQtxzo/Y9BnzO3bsCY4HXwu1fBQqAXgS1fd8AjliI\n2d0fA24F3nP3Lu7+nej9FvRfe4FgcelBQH/gychu4IdAP2AUQY3X/eF1bwDygMvC6/6olnt6Mixf\nP+DjwA/M7Nyo/acBe4A04HlgMHBbJCiY2XAz6xweW0TQHJpB0OQ5HKg0s5EEzZ/nAReHx90CHDCz\nrgTP4SXgU8BC4HUzi3xfW2opc7TrgEuANHcvBz4CzgC6A/8J/MHMMsOyfiL8bm4EuhHUuO4C/gDM\niAq/7YBrgd/V87lXAzPC72M88OmaB5jZCOB24JTw9+IigtrWlwhqf58Kn8uE8JRjPYtZwNMEz+In\nwBthOSJuAJ5097J6yi3SJinEibQuPYCd4V/8MXH3X7t7ibsfIggDE8IaPYAyYLSZdXP3Pe6+JGp7\nJjAwrOl729396KvXawrBX+x3hTWGpZE+e+6+3t1fcfdD7r4D+ClwViwXDWvCpgN3h9dcRlAjeGPU\nYf8GdhCEVgvvZQ2wxMxWAf9HdZ/hze6+K/xObwOSw2PnhN/DY+7+PvAIQXD6OXBpcBv+E+BPBDV2\nvyIIwYuAYzUv/9zd8939YPh9/Nndt7h7pbs/BXwYfn8AnwF+5O4LPbDe3XPdfSvwFvCJ8LgZBL8b\ni4/xuVvcfTfwN4LwWlMF0IHg9yLF3Te5+0e1XSzGZ/Geuz8X3ttB4HHgk+H5yQSB9vf1flsibZRC\nnEjrsgvoGWvfIgtGZc4Jm+r2ApvCXT3Dnx8jqGXKNbM3zezUcPt/A+uBf5rZBjO75zjKOgDIrS1w\nmlkfM3sybLLbSxCOeh51hdr1A3a7e0nUtlygv7tHBj9sdfdzw9qihwlqze5z93HuPtbdz3H3Ynd/\nA3gjbKosBrYThLjPuvsV4bX+CuDud7v7KHefHd7bX8Lt7u53hdcdR/gdu/sbkYEV4fvb3f234dv8\nGt/HjRaMfC0ysyKCWtHI9zGAoKauNlWBKPx5rDC0Ler1AWoZLOLu64EvEQT+wvA59avjenU+i6j3\n+Ueewl8JAuJggkExxe6+4BjlFmmTFOJEWpf3gEPAFcc6MHQ9QXPW+QRNdYPC7QYQ1u7MImhqfY6g\nVomw5u6r7j6EoPnuK2Z2XgPLmg9k1xE4f0DQPDvO3bsRBJDo6Tfqq/XbAmSETZoR2cDmBpYPMzsD\n+DpB8166u6cBxVFlyQdOquXUfGBIHZfdD3SKet+3lmOq7s/MBhLU4t0O9AjLsCqGMkDwzMab2ViC\n2sG5dRzXIO7+hLufTjBwxYH/qlnuUCzPomYzfCnB79knCZpSVQsnUgeFOJFWxN2LgfuAB83sCjPr\nZGYpZjbTzGrrO9aVIPTtIggWP4jsMLP2ZjbbzLqH/ZH2ApXhvkvNbKiZGUGoqYjsa4AFwFZgjpl1\nNrNUM5seVa59QLGZ9QfuqnHuduoISe6eD7wL/DC85njgZoLavIbqCpQTNL22M7P7CPqdRTwKfM/M\nhllgfNgp/wUg08y+ZGYdzKyrmU0Nz1kGXGxmGWbWl6BWqz6dCYLODgAz+w+CmrjoMnzNzE4OyzA0\nDH6RQPQ08ATBSNi84/gOjmBmI8zsXAumYikFDlL97LcTDARJCj//eJ/F7wj6412OQpxInRTiRFqZ\nsB/WV4BvEfzFn09Qi/NcLYf/jqB5azNBP695NfbfAGwKmzRvpXpU5TDgXwRB6z3gl+7+egPLWQFc\nBgwlGKhQAFwT7v5PgvnZioG/A8/WOP2HwLfC5sWv1XL56whqFbcQNGt+x8M55RroZYLBCR8QfE+l\nHNn891OCWqN/EoTcx4COYfPhBeH9bSPow3ZOeM7vgeUEzar/BJ6qrwDuvoagw/97BCFpHMEAi8j+\nPwPfJwhqJQTPOSPqEo+H5zRWGOpA0B9wJ8G99QbuDff9Ofy5y8wi/Scb/Czc/R2CYLjE3XMbqdwi\nrY41vC+yiIi0FGaWDawD+rr73kSXJ1Zm9hrwhLs/muiyiDRXCnEiIq1U2Kz5U6Cbu9+U6PLEysxO\nAV4BBtQYFCEiUTQ7tohIKxTOc7edoBl4RoKLEzMze5xgYM4XFeBE6qeaOBEREZEWSAMbRERERFog\nhTgRERGRFqhN9Inr2bOnDxo0KNHFEBERETmmxYsX73T3Xsc6rk2EuEGDBrFo0aJEF0NERETkmMws\npvkR1ZwqIiIi0gIpxImIiIi0QApxIiIiIi2QQpyIiIhIC6QQJyIiItICKcSJiIiItEAKcSIiIiL1\nKS6ApX+AZz4D21YlujRV2sQ8cSIiIiIxO1gEm96GDW8E/+1aH2zv3AvGXAV9xyaydFUU4kRERKRt\nKz8E+fNhw5tBaNuyBLwSUjrDoOmQcxMMORt6jwazBBe2mkKciIiItC2VlbB9VXVNW+67UH4QLBmy\ncuDMu4LQ1j8H2rVPbFnroRAnIiIird+e3OrQtvFNOLAr2N5rJJz8qSC0DZwOqd0SV8YGUogTERGR\n1ufAbtj4VnVw27Mx2N41E4ZdGIS2wWdBt8zElfEExTXEmdkM4AEgGXjU3efU2D8buBswoAS4zd2X\nm9kI4KmoQ4cA97n7z8zsfuCzwI5w3zfc/R/xvA8RERFp5soOQt686tC2dTng0L4rDD4Dpt0WBLee\nw5tVv7YTEbcQZ2bJwIPABUABsNDMnnf3NVGHbQTOcvc9ZjYTeASY6u7vAxOjrrMZ+EvUef/j7j+O\nV9lFRESkmausCIJaJLTlzYOKQ5CUAgOmwDnfCEJbv8mQ3DobHuN5V1OA9e6+AcDMngRmAVUhzt3f\njTp+HpBVy3XOAz5y99w4llVERESaM3fYvSGqX9tbUFoU7OszFqZ8Nght2adChy6JK2cTimeI6w/k\nR70vAKbWc/zNwIu1bL8W+GONbXeY2Y3AIuCr7r7nRAoqIiIizdC+HcEghA1vBNN/FOcF27tlwahL\nYcg5MPhM6NI7ocVMlGZRv2hm5xCEuNNrbG8PXA7cG7X5IeB7gIc/fwLcVMs1bwFuAcjOzo5LuUVE\nRKQRHd4Pue/BhteD0LZ9ZbA9tXsQ1k7/YhDcMoa0mn5tJyKeIW4zMCDqfVa47QhmNh54FJjp7rtq\n7J4JLHH37ZEN0a/N7FfAC7V9uLs/QtDHjpycHD/OexAREZF4qSiHLUurm0jz50NlGSS3h+xpcN59\nQRNp5kRISk5sWZuheIa4hcAwMxtMEN6uBa6PPsDMsoFngRvc/YNarnEdNZpSzSzT3beGb68Ems8i\nZiIiIlI3d9j5YXVo2/Q2HNoLGGSOh1M/H4S2AdOgfaeEFrUliFuIc/dyM7sdeJlgipFfu/tqM7s1\n3P8wcB/QA/ilBdWi5e6eA2BmnQlGtn6uxqV/ZGYTCZpTN9WyX0RERJqLkm3Vy1lteANKtgTb0wfB\n2KuC0DboTOjcI2FFbKnMvfW3NObk5PiiRYsSXQwREZHW71AJbHqnOrTtWBts75gBQ86qnmQ3Y3Di\nytjMmdniSKVWfZrFwAYRERFpoSrKoGBRdWjbvAgqy6FdKgw8DSZeFwS3PuMgKSmxZW1lFOJEREQk\ndu5QuDZq8fh34PA+wKDfJDjtTjjpHMiaAimpCS5s66YQJyIiIvUr3nzk4vH7wokiMk6C8deETaRn\nQMf0xJWxDVKIExERkSOVFsOmf8NHrwfBbdeHwfZOPYPANuTsoH9bmuZhTSSFOBERkbau/BAULIzq\n17YYvBJSOsHA6XDyp4Pg1nu0+rU1IwpxIiIibU1lJRSujurX9i6UHQBLhv4nwxlfC0Jb1inQrn1i\nyyp1UogTERFpC4ryqkPbhjfhwM5ge88RMOmGcL626cESV9IiKMSJiIi0Rgd2BysiRILb7g3B9i59\nYej51f3auvVLXBnlhCjEiYiItAZlpZA/rzq0bVkGOLTvCoNOhymfC4JbrxFaPL6VUIgTERFpiSor\nYNuK6tCWNw/KSyGpXTBH29n3BqGt/2RITklsWSUuFOJERERaAnfYszFqvra34OCeYF/vMZBzcxDa\nBp4GHbokrpzSZBTiREREmqv9O4PJdSPBrSgv2N6tP4y4JJxk90zo2idxZZSEUYgTERGJQWlZBSs3\nF7M8v4h9h8rj8hntKkrpv3cpA4oWkF20gN77PwDgUHIX8tNyyDvpWvLSplCUmh30aysECouB4riU\nR4528bhMhvfpmuhiAApxIiIiR3F3CvYcZEneHpbmFbEkbw9rtuylvNIb9XOSqWCcbWR60ipOT1rF\n5KQP6GDlHPJ2LK4czm8rr+adyrGs8sFU7E+GzQCHgfWNWg6J3dDeXdpGiDOzGcADQDLwqLvPqbF/\nNnA3YEAJcJu7Lw/3bQq3VQDl7p4Tbs8AngIGAZuAq919TzzvQ0REWreDhytYUVDEkjCwLc0rYue+\nQwB0TElmwoDu3HLmECZnpzMxO40enY9zAlx32LU+7NP2Bmx8Gzu0N9jVdzwM+Tw+5GzaZ0/j1JRO\nnArc1Rg3KK1S3EKcmSUDDwIXAAXAQjN73t3XRB22ETjL3feY2UzgEWBq1P5z3H1njUvfA7zq7nPM\n7J7w/d3xug8REWld3J283QeqatiW5O1h7dYSKsJatsE9O3Pm8J5Myk5ncnYaI/p0pV3yCSw1VbL9\nyH5tezcH29OyYcyVVf3arHPPE7wzaWviWRM3BVjv7hsAzOxJYBZQFeLc/d2o4+cBWTFcdxZwdvj6\nceANFOJERKQOBw6Xszy/uKqGbVn+HnbuOwxA5/bJTBiQxm1nncTkgWlMHJBOxvHWskUcKgmWsYqE\ntsLwr72O6TD4LBhyVxDcMgaf2OdImxfPENcfyI96X8CRtWw13Qy8GPXegX+ZWQXwf+7+SLi9j7tv\nDV9vAzQkR0REgKCWbdOuAywNa9iW5Bbx/vbqWrYhvTpz1vDeTB6YxuTsdIb36Upy0glOfFtRBpuX\nwIbXg9BWsBAqy6FdKmSfCuOvCUJb3/FaPF4aVbMY2GBm5xCEuNOjNp/u7pvNrDfwipmtc/e3os9z\ndzezWnuZmtktwC0A2dnZcSq5iIgk0v5D5SzPr+7HtjS/iN37g1q2Lh3aMXFAGl84+yQmZaczcUAa\n6SdaywZBv7Yd71fXtG36NxwuAQz6TYLT7gxC24CpkJJ64p8nUod4hrjNwICo91nhtiOY2XjgUWCm\nu++KbHf3zeHPQjP7C0Hz7FvAdjPLdPetZpZJMMD6KGHN3SMAOTk5jTucSEREmpy7s3Hn/qrBB0ty\n9/DB9hIiA0aH9u7CeSN7M3lgOpOz0xnau8uJ17IdPgA71gVNotvXwPZVsH119eLxGUNg/CdgyDnB\n0ladMk7s80QaIJ4hbiEwzMwGE4S3a4Hrow8ws2zgWeAGd/8gantnIMndS8LXFwLfDXc/D3wKmBP+\n/Gsc70FERBKkpLSM5fnFVU2jS/OLKDpQBkDX1KCW7aIxfZmUncakAel073QCS0tVVgarIUSHtcI1\nwaLxXhkc064j9B4Jw2dA9tSgf1v6wEa4U5HjE7cQ5+7lZnY78DLBFCO/dvfVZnZruP9h4D6gB/BL\nCxbjjUwl0gf4S7itHfCEu78UXnoO8CczuxnIBa6O1z2IiEjTqKx0NuzcHzaLBk2j728vwT2Y03ZY\n7y5cNLpvVV+2k3p1Iel4a9n274LC1UeGtcJ1ULY/PMCCQQd9xsDYj0Of0dBnLKQPgqTkxrplkRNm\n7vW3NJpZj+hmzpYoJyfHFy1alOhiiIhIaG9pGcvyiqqm+ViWX0TxwaCWrVtqOyZlpzMpOwhsEwak\n0b3jcdSylZXCzvePDGvb18C+bdXHdOoRhLXeY8KwNgZ6jYT2nRvpTkUazswWR+bHrU8sNXHzzGwZ\n8BvgRT9W6hMREYlSWel8tGNf1WjRpfl7+LBwX1Ut24g+Xbl4XN+qedmG9GxgLVtlJRTnhWFtdXUt\n26714BXBMckdoNcIOOnc6rDWewx06R0UQqQFiiXEDQfOB24Cfm5mfwJ+G92HTUREJKL4QBnLCopY\nkrunqpatpDRYazStUwqTBqRx6fh+YS1bd7qmNqCW7eCeIKAVRgYZhK8P76s+Jn1QENBGXw69w6bQ\njCGQ3CwmZBBpNMf8jQ5r3l4hmObjHOAPwOfNbDlwj7u/F+cyiohIM1VR6awv3FfVl21JXhHrC4NA\nlWQwvE9XLpsQBLZJ2WkM6dkZi6Xmq/ww7Pzg6LC2N2qSg9S0IKBNvL46rPUeCR2ax7qWIvF2zBBn\nZj2ATwI3ANuBOwhGiE4E/gxoymkRkTai6MBhluYXsTQ3CGzL84soORTUsqV3SmFydjpXTAxC2/gB\naXTpcIy/ZtyhuODosLbzg2DCXICklKCf2qDTq8Nan9HQNVNNodKmxVK3/B7we+AKdy+I2r7IzB6O\nT7FERCTRKiqdD7aXVE2kuyRvDxt2BCM4kwxG9u3GrEmRWrZ0BvXoVH8tW2kxFK49MqxtXwOHiquP\n6Z4dBLThM4J+a33GQI+hkHwC04eItFKxhLgRdQ1mcPf/auTyiIhIguzef5hl+cHggyV5e1ieX8T+\nw8HAgB6d2zMpO52PTc4KatmyutO5rlq2irJgUMH21eFAg3DAQXHUSowdugdhbdzHq8Na71GQ2r0J\n7lSkdYglxP3TzD7h7kUAZpYOPOnuF8W3aCIiEi/lFZW8v72EJXlFVfOybdwZ1LIlJxmjMrvysZOz\nqqb5yM6opZbNHUq2Hj2Fx873oSJY+oqkdtBzeLAEVc5NYVgbDd2z1BQqcoJiCXG9IgEOwN33hOuZ\niohIC7Fr36GqJtEleXtYUVDMgbCWrWeXoJbt6pwBTM5OY1xWdzq1r/HXw6F91U2h0asalBZVH9Ot\nfxDQhp4bDjIYHQS4do2wXqmIHCWWEFdhZtnungdgZgMBzRUnItJMlVdUsm5bSdVo0SV5e8jddQCA\ndknG6H7duDpnQFUtW1Z6x+patoryYKmpmmGtKLf6A9p3CQLamCuqw1qf0dAxPQF3K9J2xRLivgn8\n28zeBAw4A7glrqUSEZGY7dx3KJyTLWgaXVFQzMGyoJatV9cOTM5O4/op2UwemM7Yft3p2D45aArd\nVwjb34N1UWFtx/tQcSi4sCVBj2HQfzJMvqF6VYPu2ZCUlMA7FhGIbZ64l8xsMjAt3PQld98Z32KJ\niEhtyioqWbt17xFNo/m7DwKQkmyM7teda6cMqFr9oH9aR6zsQLA2aOE7sDaq/9qBqBUVu/QNAtrg\nM6un8Og5AlJSE3SnInIssU5fXQEUAqnAaDPD3d+KX7FERASgsKQ0WKoqHHywYnMRpWWVAPTp1oHJ\n2encOG0QkwemMaZvF1L35VdP4bE2DGu7N1LVCyalUzAKdMTF1WGt9xjo3CNxNykixyWWyX4/A3wR\nyAKWEdTIvQecG9+iiYi0LYfLK1mzdW91X7bcPWwuCmrZ2icnMaZ/N2ZPHcik7DRyelbQt/Qj2D4/\nWCt03eqgtq08OB5LCpaa6jMWxl8bhrXRkD5YTaEirUQsNXFfBE4B5rn7OWY2EvhBfIslItL6bd9b\nypLcPSzNDwLbys3FHCoPatkyu6cyOTudz0zry7SuOxlKLik7/x3Usq1dA/sLqy/UuVcQ0HJuqg5r\nvUZC+04JujMRaQqxhLhSdy81M8ysg7uvM7MRcS+ZiEgrcqi8gjVb9laNFl2WV1Rdy9YuifH9unLn\nxGSmddnJcMuja/H7QZPo+o/Ag2BHu9QgnA27sDqs9RkDXTTrk0hbFEuIKzCzNOA54BUz2wPkHuMc\nAMxsBvAAkAw86u5zauyfDdxNMOq1BLjN3Zeb2QDgd0Afgo4cj7j7A+E59wOfBXaEl/mGu/8jlvKI\niDSVrcUHq/qyLcnbw6otezkc1rKN6l7G1b12MyV7G8PIJWP/hyQVroPC/eHZBumDgoA29qrq9UIz\nBkNScsLuSUSaF6tjRa3aDzY7C+gOvOTuh49xbDLwAXABUAAsBK5z9zVRx5wGrA0nEJ4J3O/uU80s\nE8h09yVm1hVYTLB265owxO1z9x/HWu6cnBxftGhRzPcpItIQpWUVrN6ytyqwLc0rYmtxKe0pY1S7\nrZzfYyc5Hbcy1HPJ2Lee5P3bqk/umBG17FRYs9ZrJHTokrgbEpGEMrPF7p5zrOPqrYkLg9hqdx8J\n4O5vNqAMU4D17r4hvNaTwCygKsS5+7tRx88jGDyBu28FtoavS8xsLdA/+lwRkUSpqHTe+mAHb3+4\nkyV5e1izpZjelYWMsDymdNrGzR23MKRHLmkHcjGvgGJgX3voNQKGnlM9OW6fsdClj5afEpHjUm+I\nc/cKM3s/esWGBugPRK12TAEwtZ7jbwZerLnRzAYBk4D5UZvvMLMbgUXAV919Ty3n3UI4KXF2dnYD\niy4icrTCvaU8tTCfP83fwMR9bzG93Tqu7rCFQam5pFaETaHlQHI29BsLva+qDmsZJ0FyrLM6iYgc\nWyx/oqQDq81sARDpsIG7X95YhTCzcwhC3Ok1tncBniGYYHhvuPkh4HsEfeW+B/wEuKnmNd39EeAR\nCJpTG6usItK2VFY673y0k7nz8nhv7UausX/xXOor9Gi/E0/tjvUeA32mV4e1XiMhtVuiiy0ibUAs\nIe7bx3ntzcCAqPdZ4bYjmNl44FFgprvvitqeQhDg5rr7s5Ht7r496phfAS8cZ/lEROq0a98hnl5c\nwBML8ijflcttqf/kgdTX6VB5AAacAafdgQ29QHOuiUjCxLLsVkP6wUVbCAwzs8EE4e1a4ProA8ws\nG3gWuMHdP4jabsBjBIMeflrjnMywzxzAlcCq4yyfiMgR3J2Fm/Ywd34uL67cxojK9fyg+yuc2vHf\nGGBjroJTb4d+ExNdVBGRmFZsKKFqvRbaAynAfnevt73A3cvN7HbgZYIpRn7t7qvN7NZw/8PAfUAP\n4JdBbqM8HI0xHbgBWGlmy8JLRqYS+ZGZTQzLtAn4XAPuV0TkKMUHy/jLkgLmzs9jfeFeLkldwT/T\n/8mgfcvAu8Gpn4ept0L3rEQXVUSkSkOnGDGCEabT3P2euJWqkWmKERGpyd1ZXlDM3Hm5/G3FFrys\nlC/2XMQn/e90278Rug8IgtvkG9XHTUSaVKNMMVKTB4nvOTP7DtBiQpyISMT+Q+X8ddkW5s7PZfWW\nvWS138eDme9x1t6/0m7fbsicCDMeg9FXaDSpiDRrsTSnXhX1NgnIAUrjViIRkThYu3Uvc+fn8tzS\nLew7VM75vYr42dBXGbr1BazwEAyfCafdDgOna942EWkRYvln5mVRr8sJ+qHNiktpREQaUWlZBX9f\nsZW583NZkldEh3bGnSdtZ3bF86QVvAYHU2Hi9XDqF6DnsEQXV0SkQWIZnfofTVEQEZHG8tGOfTwx\nP4+nFxdQfLCMYT078JucTZyx40na5a6ATj3h7HvhlM9A556JLq6IyHGJpTn1ceCL7l4Uvk8HfuLu\nR02wKyKSKIfLK3l59TaemJ/Hext2kZJszBrZhdvTljLww99hqwqgxzC49Gcw4VpI6ZjoIouInJBY\nmlPHRwIcQLhY/aQ4lklEJGb5uw/wxII8/rwon537DpOV3pHvnt2Nj5e9QKeVc+GjEhh0BlzyExh2\noSbnFZFWI5YQl2Rm6ZH1Sc0sI8bzRETioryiktfWFTJ3fh5vfbgDA84b1YfPDdvLyZvnYvP/Ehw4\n5spgsEI//btTRFqfWMLYT4D3zOzP4ftPAN+PX5FERGq3rbiUJxfm8eSCfLbtLaVPtw7cec5JfKrn\n+2Qs/w68/G9o3xWm3RbM8ZY24NgXFRFpoWIZ2PA7M1sEnBtuusrd18S3WCIigcpK560Pd/DE/Dxe\nXVdIRaVz5vBefO/Skzj30Gskz7sH3v0QumXBhf8vnJy3e6KLLSISd7EMbJgGrHb3X4Tvu5nZVHef\nH/fSiUibtXPfIf60KJ8/Lsgjf/dBenRuzy1nDmH22E5krX8CXvoVHNgJmRPgY4/B6FmQnJLoYouI\nNJlYmlMfAiZHvd9XyzYRkRPm7szbsJu583N5efU2yiqcaUMy+PpFI7mo717aL3gIfvsklJfC8BnB\nYvSDTtfkvCLSJsUS4syjFlh190oz08AGEWk0RQcO88ySzcydn8uGHfvpltqOG6YN4vpk23H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W9cPJKZY48zuAGUbIM3fwRLHoekdjD9Tpj+JeiU0YilFxERObZYRqcWEiyZJdKsbdy5P5gOZMVW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\n+n+49EdNkk2SlgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd246f79fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the loss function and train / validation accuracies\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.title('Loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Loss')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(stats['train_acc_history'], label='train')\n",
    "plt.plot(stats['val_acc_history'], label='val')\n",
    "plt.title('Classification accuracy history')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Clasification accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SXUdcKe5XLrANlfIyAmI+CMW2w2hlGwyqKJQB2joGxvBOYwaKPPVd\nyiYg1dK+PpUVOhPnnEKezFY1G8Jqiv3d0LodhQLb6DGnsBGqfWnH3eR9MfFu3+K6RN5YRlZcRJwt\nTiD1GPcabs9N4/omaedWDamHpdUI0mLTclztRE+F66PrqgJUCvLwZR8DZrJyAE4dK5LXs1ZkbvO7\nCkMSmRKNm0/zWQ2IoNzCbdAq+Q00ZBjgF6yb2LPIgLgUowP4u9txT5DOX5Gv19Ttr8/wvb+sH8Qf\nuRisPvdXf4YnWhn4/mRtFVstXO+19dFBbt34ZfTcywrAztFFjIh1lGxJgSYXJ9z7nmMgWrn/NnqV\nYi/t8hkcEAdafOcDe2CZ5IR+Ys9PAQB/e383BpZJETbvXkVPkQHcLXdjREX63XyNVP532j8F0xyr\neadLyZq6rXY6UIgyMDWESE9txIAKBH2MIOJVJjnNFSNCU3yOxM3vKgtZKIJCN1cU8pi46lClQGST\nfTQsKt4rEQ8KOg5cdVIHZZYDZFRXhi3HyTshrjyUKO2IiMGWaHTBKG5QycR1QCe/s5bn7x3i7Nb/\nKBGNDdNJUrd7/BxgS8Pfwy8LSv565Di8ca7NGSQxuHZxdilf4ne9P3oVP4K40tDshsHKAb9D7cW2\nBNOYkoGbtZe+F8aeYVJy6c3ryIoLyHXKlyEdpd+Pi2NOdcUwvBImgPOpH2Js9XcBAA/5vwyZib5q\nnWRCVfhYU03dzLYhfNrP9jz3Fv1f9aEQKlvihqWjAZQSnDgsxYtYqNJGDWUevrK/vImLDnHIQvWj\nCD/F/eDHdiwjLWh/uYb/X2icxcUgx7TvbAmpNVKwHV439p5lkjLwBU5kodU92LRzndr+ob2YvE3/\n3X3qs3jBwzXp33EzuM69XXstNHQuDbOozHepSUu/+LAdg2vcY2t9KIPICvc7Z7uewdDpxwEAS5/h\n3l2vCriWZSBuDtsws5v+qVD8EJZ/5C6A9L30Y/eOFfSLfbzPn5mHqoc05tDSBBa0pFOl2xlXNLL7\n0Puv4rak/Q8CenHzzexriEgY06ZOSTBwWFxT+eqdujmbUlgfp/1KjYcxK6GPb+b5rL6GAmTiQnuD\nQgdE+P+lVTucTk6cpRNiDE70o1rl2J2RJKCOcgwlMxFUBMixdbAvlQtVOFdpk6KygE2IY32rdoQK\n9PGKRJzlnIxDmqYvxzwZVOABAOR7GzESqX1bFgDkUza4bXzucriEsofvy8wwnvmNenha+P+5VAmV\nsjgGcqCIaoS+lpBSN0UlD1uav+uAFNMlJnbKaguyYSaG3VouYa2sdWNTR//ON6YQLYgDMhqyKImz\n1LUuPj9taIN3TOyWULngzbMvVg6lIN+ofaDL3aRONdelLnWpS13q8h7K+wLxqvqIarbammC5TJQK\nrxNz15mBG3vs6BaXsWsSYp+a2QJlihnHonYKewXyDOx2IHya2U6mgXSuvShBOkFVpVUl8oLGXPNU\ngWseAEBlOzPC5NwkkimiVLPdgoKERQclawWno4ISVzO7+9D2CK6JbF6bddXU7RfHmeUWdzjh3WCG\n7x4+iSt/QTqr4Rck6AyzoEndSGqteXgUMypm9DOFndi9j9l6+28FcE7O7Cz+MJFk4cc96PqkoI91\nh/GqgZTHiXMp/KOeqKavmcjH8pIGs4LmjR1PYPU8M+3POxugWCJif2WAVaef3PomktPM+C7Nemrq\nZp9RYLmNqCQpLknQKTehF5dYT5fi0FmIzvxLbTB7BF0oIQVWyJeQauGygHJZjrK4X1SecqBHw76d\nTIqTetJ6VGX8XTUfglHs/7X48siaiDpSGhZBbeXn0aYXh5n7ikiL40JDLXG0S5jlx0xsbzRf++Qq\n2eVxyB+kT0w8Rz9s8A/jgIqZbXouC39GFGoZQxh7mv51Tx/bGDB24HEHKx3XApu44qfPaY9qUWri\nEkDpNtHCAWcKBi8LPM4rB9C58QIAYDXwEM4ZlgEAx0SRn8UdQ87AfuvwHUFVSX3W3n4QLZv0mXAX\naW9V4KWaujlMUfzx1+ivLf9Am1tOjeGK/j/x/wvzCASIPC3pCO5tJ8qcuk3kcLH7MLq/T9/a6t9C\n70c4fscut+OYuFDhUol18LGfAO6vfo7f/fApBO0cWw2Dt3GxQPbGFKXPVRSnsdhMtir/l3L0Pkw9\nx0omfFpUmF+f5Gc3K18FcPoO3ZT7JIh2kC3yFXiz0L6VCYTcpAvzPgu6dETuLb59sO1ijLi8TmZh\nSetA/xaRk7dqhDIi9FlqRdtf067Ba18CAPS8HsLyY/Q577AKLoFGn3KF8aVefj55hezDkcwCkl3n\nAADxxrPoFYjtjXU9pErGkM1tC+jJ3v1eV99FGZqCHMvNw5PQVMXNZ3nSxKm1eYRDZEYMEj3sUnHy\nkiuN3JpAbRpire0raSj3ctz4ggokpBwH+xIF+MSpW69vkRELJC04JFiqG/EAmkP8XdX4NnQeFkRG\nZzlWsmE7MmIP/ZSvjH3t7Lf4FQ062muzSwCQt1aR83NMdiW7kHeK276SghlIXkKTuKTjikECjaC+\nTVeH4HBy+S22yRPF7MUI0hrB0ql92GMkrfyWdBVGKcdy2kn/d2dHsAE+15GSAXKOw2qyhOA0Ef+V\nKY7TzgEj7OI0sIw0gHWb2Me/aUWu6e661ZL3xcS7Pk1qqBpwoVFDvn5tMYWhndyQ7ps7Cn+ZjmET\n+pXm9HA30LhHA0XMikMS9Be8SLlYMViWksKVWBxIiSrIaimAoNgAHvRHsdPLdbHYPD/z9B1DQsHO\njgdlKAXpOPuzKZzLsQ2tatKxzy3m8Ig4nnKy0FJTN9lnSUG+lhrEX+0kVf3UaR0sf8YtI+2v90Ei\nyvpHFkj3PhmsQqfwAABUA0WYnuKkGDz2VfS5+IzEZdI20pMBnHuKk1BLrx1a/7MAgDHJb2J4iVTx\ngqi4a5Q9gtUSA9fw1TS811kRe1GtgKmZz02OkeNSlDtw+WNMdhKna1fsrdsSMPg5QBa2cdA45p2Q\niY3uenUGST8HiCwbgyFBu2mzDOQrnePILfLvtsYCsgr+nZT6kFExUCrFYSaRqg56UVSuKeuxFhSV\n0QY70n72S9nGQdWhkKMwSZtt7lTCXuXEIMlWkRbV50owoDam8jV1s+vy0K16AABNej7f0L2Ff/ou\nA+N9h2wo3iRlvOnuwMAcD0y4MsWgr1RI4UiYhZ6tMFnElWeaVpQuca9DSfVhAEAhfwaVadr6SUkr\n5o5xXVfaehOhPN+XEdWjjQu3IDfxXf7OKvaKrRTqL+nxwgLXT00J+vJjk7aauik7WlD8bdKQtmtM\nCF6UPY6PtDPBa74YxUiRyetqjxOFVfZBNMakbmFlE5EnGZQPvfkcYhbS6/3aVnxfTbtq9dTB+4cp\nNI/yZjGttwfG5zm+PS88hhdEZbo6wmWXQEUD+0vsj/DvFBH8ESfFHTIrntlgcPR7SYG3t50GvnOn\nbvPvtGHATwo/VeFE2Ba2wZSmPw3eD5wd/NlBDBrI1Zz0TZP8rEfzJnQl9kvqF7VoTzE2fXLWjuvr\nDMCPWOln554w4MQtToTJW0rkhpYBAL8qK6CQFj6zk3T35QkddmsYa8pyIxw5Ji5H5XZcGGC8emC9\nBavuuxSLAFjPTaNn0MO2LcnwrIwTnHNJ3KzU2gqDuC1xtf2nmBxn4tcUi6FJHDzkL/LfLdcgtqY5\nRhr0w1CK2pqV5TjyXo6X1iT7Utosh18nts6spBF20idXin3onBKTVifjZNm4ggC45mwtrOO2lOPU\nZDUhXrj7Wc0VK1AOsO/PWfxIi1tWG8UM5Usfgr9FHA05XUK8nXFlrvk2jmaZNKUjTDRjO+xwzNMQ\nGkUVqSgTrWG1DCsafi4Xw356LYsy6NeVgWsIjnLMbLXIEd/Ol1vNtHNpLohbWk7GlmwFa3razFk2\nwFXQ3FW3WlKnmutSl7rUpS51eQ/lfYF4015m7frAFCYrYj9ZSwbKGKkog7L8f+/33LzGbEw/MI1o\nnFnGqkMCSYQUwFTwBgZEEY4qSxTnc1yB/xqzv4bdKeglRMfmhSrCanFQg1wcqVaeh2yTZikXddCJ\n3ORWpgmN28W9j0W+15vbgdUQEaR5R+2M56U032v/ejd+8BUWoYybn8Lel4lyO/9Ii2f+gsjeeIEI\n6XR6GsUcC8vSRTdUnyb9tlM/j+Qas27Np7gR/MeNX8SFFP//z4wVDG8n3bIZ+gYyRt6Wsu0W92f+\nwDGPPzvLowlP7RyHTs79vzuH9uO1ftLgpq+JCwX2qaCNMJOc/4V7gT8/d4duVmsF4QQz3sYgM3i/\nRIpFI/vT7M9CYWW/VZv0kKdoq3kFbaX1OdBQJtLwSdWQBUVG29aM9CL7IGESh76rKpCJw9kXS2qU\nxP230rU8ZE5+XoyTDkk2SbDVT2RlLRghl/K9CqsGlTRhszTNrH1dp7hDLwDw3diPB7cxi3/GTjr8\n+FoIx3bxmMfUrZswlj/LNlY2kPWQ2agImk4WuozpedKqA9JOKCv8/7dKH0TvIDPo0A3av+K+gYyO\nfrIuqcBSph7t14vY8tF+2gfp91dGH0XXx9jm3PksrrtJja3P6rEzzPaum9iGVZWnpm6p1Vkcj4vb\nrSSkmh/pi+LH59mufEyJpJ1j55CzCZvi4ni1nqjRlRjHduGrS0u7oXqIY0hS1sK9wufqQ/z9tpEE\nJHvo65fPOFFqINJ+u/M6ts3Q7/tlTwIASsk2BMXlB64/78FfOJcBAMeOW7EvSz+5PMJLR6z31q6Q\nfdw9izNatqc6Rjpx/nAUsRztZ08HADPp3x3qn+JqhIjfcZuMw+Cuj2D9IIvbWseuQi1MeO6Jdniu\nkhEYb+aHu/65iOoHyGS89hstOOznUZ+q1asYmToHADga/QUAQPMnssi+QP9+IFPB18Rta9vUMngz\nrCy/3T8F75m7o0JF5xDCFiL04JVrOLiXY2Spiyjt9rUF7LBSH3XJhqSeTMXSghbNdrFLoMSlkBF/\nBp1lIvAZ0zQMGfZn474KIlGOjcQkmZPQEwoYxE1cq5kAusStPYYeC9byfEdAIHzbbT0snUTwTbpm\n3MoTYRYSMpQktYv9AKAUzeGiikjZde5ZRI+y4j1lJmtXVU2jKMZuQroJTSNj3sBqK+JhxsRlpYe/\n1wYxZiIL4NqSw8PibIwua+EQZ3g4WGMKn04JSZl971sZRNFDKOzayEMtjrtFC30nXZWgQxQYOhWH\noJSwL+yeDFSm2mcd3E3qiLcudalLXepSl/dQ3heIt0kp7uBdOAFjC8v60y+n4RxkZl80NeJWidlH\nzxEih3D6CHLSZQCAvuxGVsMs19tyATEVy9mtWa6ZWkPDUDAZhWwiA8k+ZkulXToYEwKpiexGZjID\naeYj0WgMVRmLFVqS8ygpRdHWJvf8tehTCB0l4tM5l2rqdrREZHbuM9+G6qd81vaqD+94uR73zg8D\nGNjFjEruIBJUxk3wi/Pfl+99HrpbZAFmWkq49j/EMWaf/QQA4Oe/fh0P/T7f4csmkRQn4rTN/hba\nMmcAALcFGP/UqgtfayZKK479BkZ2MBs98fYXcEbCbSm/9ylmcaPd59Dzdeo75b1VU7dSoAlyMFuM\nzTGDdztj8Iuj+vQtOZTF2eElWQTxKlEQTMxQddUiTGVmwdWoBBB38MbLCWTcRJl9a+JUKkkrfFUi\nBq1ciek1rjl1O1pQKtBP4nb+vpIFWrMe6tmgQDzOPnImlUgIdKyQ8vmZfLWmbp8+vITL4vq9Dj39\nYVohh6FIfXWIYtlGdJdTvIrd4t7R1BIVPqUcxKd20bdsIRc27dRzt2UGbaeJMldkRAkbS5+AQiBX\naXoNkQKRpVFmwmaLWEe6SIS37xNpLEwJhB/dCfV2sgv9rR+E9xZZELmLa+kWccLaf5SLgRJcRfaF\nqp3oZcDXiCdHWTS4pMhgrYes0Ez4Ago9RKyOfyHiWOp3oBRn5p/u3QXl34iiua/KACVZnYZerpOO\nvPYP+JZgL/6wbQRjHjIyO0I+GBY5jv5NnDjUN7cLji7q/u+2CdwvTph7aXYIXWtiG9h+rt9um7sC\n4M7tKa93reCBZfrMhd0c573yRXiitE0udxLn+0QhobyI/Sn6xkIPCxsnt59H+01xDGrIhMmbtLvx\nnhwUfdRJ72N9xqWPt8OtYv8cyE2iLc/xsqZbxMNi29nmfrIakVPd6P5P9NOffHMch70c4MmFB9E4\nSLR0+rkPwmb46zt0+pl0KJW4vS4ueOl0o1wRF5oEyO406RsRzHJcrJ9RIW9lXGiWJfCToqhhWaS+\nEqMKc01E6xltC1rcoggy1ILWeX5H/Rj9dHbLCv8u+qps0Yu5DXEJTTwGdZLo2FFhuzqP67ESIZxc\nbOuEW1x6oyqPwmTpvKtuxUwLBsT2z/zATpjF/eCQ8F1L636UFCyS8pjtkP2EiDbjmcWcOIXN2kT7\nz87Y0SDWi2NyNV67QZjb4y4hL46SfcXJmNqZUSKWpu5NphLKGeqjMMuhWeTviuJCFqXVh2KJbEjS\nDxTTtE/eX4a8mX6Lnruq+P+S98XEm1iiYuPDb2LvFAO49J453Fih43SkzqLdQGco+kh/qhuT6DFz\nwlrI5xFr5L45VbwfMi87ZWGZRlY1SGGLcXJXuXbDNMK/Y11yRJbpvM09DFZZlRYz4lzo+0N6RIRx\nk5kK5m6Q0ulrpTONLAJNJgYljNeuao4skeI52Pe3UImKTUupDZ/zClr07Qlsjnr43M/zLOd/1ZYw\nZOHE3DgXQ8cj7NRdk32QHeEkoPJzY/7Yr/Xjc6fopGu7tkMeZFB+yebEr08xUN7nYQCe8s/B+3Hq\n0Pg7t2FZEcG36SQeqLDgJ/kqJ81F8wJGjtGOhzf+ARdq6KbSJFFUcMJxFBk8x9atMKtp06RVAqmg\n+DIyKWxt4vJ5H4s2cgNxBMIMgqF0MzRxJibK5Tw0elKLaRUHvKIYRCEvJthyGHvbWBDhU4XgLIri\nKrEcoWlrRnKeE2SmYkLVLhKBSgCFLBMXlThmzlPeDeC5O3SbkYSxeU1UtKdYzNQsGUfAzc8O6WOo\ngnsB/0nzefSsMrAXblC3w184i1SJ9huQLuBKislg64IE15X0teFe9lvbzE1MJOkbmoYixq187vrE\nDnxpiHT1357jJN+e6sFeccrlSztX4a3y86r6BbwssstuE+nctdLGHXoBwH7DPSjN87hGjYYFdoua\nn0K7n5OtfKsFfa/TvtHDKbQ+S538Xax40aXtcPUwdBTm/IiIPci6L29C91viyMfRrwAAOpLHcPKL\nnECf/eddOLj86wAA+9GjSPVzgrtHyqT5nkcreKXCfq9Wy/COUp/xPh9WRHGkN/4XAIDJ6Odr6hb2\nH3/xg50AACAASURBVINsmgWCBpFcFWyP4lKEtlj3VTB4HwP0oyMunBFFlXELE6aWlWOwneA4VH3P\ni/sO0D9vSmzwGWnXNg0ThhO5LTQb+dyJSgFvdu0DAPQUpxA8zgJN+VuMQdG9jTjzHD/bf9SFzdn/\nDACI7Z3D+BTH566tt+AxCoRQ466zvM6CDhl9PB0eh3aU42lTHLWa2XET+gD7sKU3hYqBfaSeqsJj\nZpwyi7HS5NVgeYVJ+oArDUVCFCM16FHMcCJfCjHmdmypELIy3ig9Q5i2c5Ldu74XGTnvaPYZGWtS\nESMMYSZlJn8UJRvjp8bbg+hW7cNqAMApn0ZqO2NlMu6GbJ1jxKdm0t+mboFcyYkwjwYkRGGTZrMV\nw/v4N0JcngtWzXA5WfE+l+iGcYBjfnVVi8Z22qxxSRyHmbRD0suCy3BFCkM355zMlRQWxTnxZgsH\nnKrcBUOJc9WYpRmD4rCYeMAFTaR2kebdpE4116UudalLXeryHsr7AvF2O5jphBVeBDtJlSQaetGh\n4164pGYB9jlmcsVOZk3tS3pkd5Im9KbLqM5zK0rIsYRDp5l9+B5mXrFx+Swa9hK1FFqSSBSJyLRx\nOfR6ZlYt4vSsSZMfvWukndbsYWTErRytrghyZWa00qvM+Hp2AZN5ZndqY+3D9tu3iAS/t/oZHLYy\n8+pLbGDkwr8DAJ5pO4yfN/7sCDpuldgxnYdC/88AgBOafbgZZBtCW8CHtEQEV3vFsZbJp/Fdz28D\nAHrfuIXIA7SZ49krOK0kdbPRxixaMraIfW+ziOftPypg/afEsTunptGXZIHL87/KDNP9whCMWtJh\nbzZ9HsB/vUO39Yoemiai/0yMNjUbTICeKCKh6ERZ0J0NigaEssws7S5RtBGzwCVuYWqWa5CwMZtU\nZ3TYriPiugYiTFdmDaYKfcDoaIUkx6ILnawTGyuk+Y1iq1U5moPGKvYayh3I+UlRz7ltaEnRZ5py\nRKPGbO27hgPre3DESkT6wx20Q/ZsF+KtpwAA518fRjJKKr9faYF+G2mwxDCLTbK+z2KmgzTjrUAQ\nHxF0a3q7AYVusgTzGWbw4ZYsFodIcR35oQ0/Ly66mk+u4+Y6t+p89Un24UuvX8B0hD57rGsNqyUi\nsvs38mjuJXIcWSeyOmYdqqnb49kxfPcgT1n6v9h7zzA5r+tM8K2cc+qu6u6qzhGpkSPBBJAgRYqi\nSdkSLcnyyLJsjb2zjjMjyV57ZM16PfaMPbIlOSjYFiVKlEiRYgJBgACIHBpodM6hqqsr5xzmx3s1\nz+6gMM/6mWe5/FH3T/fTXfV995x7zrnnvPfcczZz9PxXJTa0n2dke9/eH+EvypzvQ9pn8GMBtenv\n8Bhi4OFLSA8ykmmxb8fyKqFXzb+xoUWgKCkjIez39inwmSXCcz9OT8P2OPl069YDsHu5hkVxxe2/\nvmzEF+5jZLa+eAdvjXAN++R6hEcZOe5YJnPk+xtH860z8yibfw0A0K3m8xP5C1jr4ve9rQnMTFFH\nOqvAxm5e/4rHP8/PbryLUyHqoe9zK8heYWZOlz6LQopRX2SWshMo+HHTy2pWQ+2T2HGbyElgYwDB\nyz4AwJrjPwEAntkbwmktk0XPX6ii8A6ryTk+8TGMxilTrx8cgjIfaEgXAMyn5dCsEsrXDdeQNNPm\nSFoYiTvCKkBKVGLe7UJfhP/P96xCnybyVPRQztK1FFqFjvgyapy28bNaTw3tE5y7q4VyFD3hgPcs\nr4eVpqfg3UM5keAC5uJMVJOmOYdQfwxVFXVXGw2jtEadtXYkEMk1RgUBQGnogl0gnLXwbehpztGm\nZBS7acshFSXfy0k3FGqiGdUBCYJztBFFcdXHaLyDzQJlVVMuwSkl7J9SXkBW3NYyjhBFnCnooV/i\nPmGozcEvo32Q6mRwimi9LSb6D3t98MtIT7sjjNUw5+ONJxC2Ge9JW6Pxgdh4JwKENixdSkRFk/oD\n+W5AXJIuJnOIdRCKU5ZpBCR9GigWyLw1xy0MmMj82w4jwnvJBHOckFKnex9mo1xJ31oB4S1kXlju\nQLuKsNJkF9+bS2+B3ELjqbgtR/hBbgzOxH7UuyjUPdu5gWaut6K7TBitWlM3pG3mEQrTc/6v4eIK\nu8q85lqF+fofAgB+R/u32BygMnx2cRkAcGaiiGtdNLjSoh1tEW4sbzjux9ynuVF86//gXP5e6kD7\nUcLEstkpJNfJB93h67AqaDSiMkImavkXEZASJtv+vTp2bKUhUJ28ga8OcaM/9CUKaf99OdwZ5e+H\nU6/hegPaOiIlhEFHqSrhWliHE6hHKVbOVBk1KYVzs5KC3UpBtpaE4hpqiIg6qMOtUdTE+VPFk8Fc\nTWTQqqjQms12KNyElNKZEjbkNPC91QxsPn4264oKeg3Q+Ql9DemAGSsV3qPLI5WgEsUsVLBYh6QB\nZYBS9zbe2aCc3N/Kd4W7c9jw82/2vVcRsvPM78DlWWhCVPpDopzeBdN5fG6Mm8z3pEV8t59HIc9a\nvojcNHl21iXa8M3WcUxFQ3zJWYS683MAgDnvq0hEKH/2f6Ist8rUaOnlMcVJpRz9RTptL0EJXYQy\n+PmtdMrOvxtvSNu3JOfhvM1neJ5mN5xQSg9LP/92KnYMW/t55CN5bRmxo3Qen9hNSDNx4T54JniJ\n9jt9c/hom2gBeLMDEi/fWUqTHxr/KbxboUwG9uow8pIoBTg4hsVJ8j6eo5wejMzhqyE6cP09dpg0\n/F7u4vPYaGE2uR/MLPbJGxeaOK9vQ4eeEKpFHHOoptewJS8co3QKXSo6g4v71NC8/hzf3UH975Er\nIR3m74Hnz6Ffz4zj5WwNklZu2PZ2bn7yw5PQrtCuXNn8AdyXeFQy1rmM/U9QP8391LHAyhAsZ+h4\n1kxvQbGP+l29cQ7OVeqLxpRBemeiIV0AIEsuoeAhVOza1ELhoD7cSZAXluQAtCJtt1dahzZOOxXr\nU2CrjrqxLDqd6XImlIc597FKFb2L3GRjYSOsdr4jrhSFTc5XsB4Um6J3ALoJUWfe3oFh+TIAICqj\nDjoX1uEUl2QL9zsxFub7CiuTkDqV96TNcSeMBS/1QWVXYumGyHcx077GVRqkPaS3Gi+jzym62PX1\noWSnE9Y+waBsNeuBdKfQf70GU3HOV9F3H+wb3LDTi6TR3VtDgRWCkaiNwHCL9kqqjKOWpN7rNPxO\nMqNEu4zrmo2acH+Mzxg3dsBWb6xr9xpNqLk5mqM5mqM5muN9HB+IiDflopc3mrVhW5pw2XibBKsC\nat5aTSEvIMG0hV5azuREh4Wejq3HgeJVerT7+hewmmWUYIox0lG3F+AQhfuL+yVwLRPabonfhEnC\nfrnKVj4rrvZDIpKzcruMeHiC0fjqhg5bTCKj2Mbkl1zbBgJ2kfGp8jSkbWONEabE84tYvcjEkt8y\nP4GKhI2yr1r60R8h3PVq8Y8572f/EZ8HPcWNATfm3iac/YX6lzH9F78EAPijQ/SZRpJ6TMbphdn9\nafxpmvDR48N1PH6bHuD3w38NABj4xB9hZo7RwPrOG3jz7/lcr/tZ9E6TJuWn6UmuRm6h9yozpy8N\nRQDc3emmLPNDk2UEWDIw8jJUK4gJONxpciAksgg7ZBIgx88mLKRNqTTCpuPcS5sKuPoEXJ0fRsDD\nNawG6XXqW/OIOikn1owX1lauy0ZmADVRhtAZFk3A9WW0mSg72cUcOreIKGtDDX2ZMG1W/LQJyPl/\nHD9cHcTvthCqrEQIpcZLLbgY43ruXbqOkcdExmppGGEBy620cw5dFSBaYOS0r3s3clXy5/sLN/CE\nnBH/x11cK+muFsj/nJHR/a4yIrcJPW5rvw/FEhOFJj7OeSl/eBVpMLEomA+i203+daoUqBco429m\nGE3tejYCvHg3bbbyCeS2iq5cp4mWrBmyGBY9nkeW7JjPi+S/khX/1shIN1skrJ2JLuBqH++Gf8J6\nGtOXRbOSigQOkP5CRUR3WR+utDLa376wDxN7KOu7EweQElXo8qs88tg72odAC/XbFnoHCQuRnupe\nJzSvs0pYXNxRNr66F8A/3kXbrxmA7CJh7pRItint6oF+lvbj9rYojrhpYxb/r8PQPcJscm+U0XVW\nZ8CNNPWmdf0wbrfymMK8M4hgjLqRsjCZTDOfx8QZ3rLwlaswPUT5feD8GpaPc11+8h0Bket+Ct0A\n7YdjrorVCiPEraEbWOpiwuiRLUuo5kfuoulnQ10sIywqwWV9eZRWeJQwWqP8qxzTqEtEglIwD4Mo\n16hqacf0Tc5NauD3FYekaFtZBgBYqp1YM/NZzrUZbIgGA8ERwvrFwCpGHyKasjZWw5SFa6xRh7A9\nS2TELRKy0qN6rM5Sd2URwLjB9/Xm26H23ru603h7HboII8iVlgJa7URM/A4iMm5zGpkU56tvD6Ig\n4Rw2b5eR1zLK724h7d0yF8ZEachVexwKK3UvaQ7B0k/d008xkl7T67FNVKhLQAOlRzR7cFUxs0ab\nFwR1xVR1A11ct4FSEGfjtDFKw204Cn33pK3R+EBsvLlZQhqRtixK4jwpZ3LjQEZ019hwYcs+0czY\nz/+3m4H5JSqpYamCml383ZpGSUayyglCP6m2cRhP8/dWywb8dgKn1YIcOXHukG4jE8OlAAZnuTG0\nWheg0gpleUiPwk0KlCTGZ+U1gK3EBUyfb3zlpu8OFRv6JL7zKZY0m1u14I/30OB9aDqLFXAxvxVi\nJt7fz9twUsHNS/oDPy7eR/jyreQePD35PQBA9xppP6ndgid3cg5TH/4JDn2P9CgfquOzPxbdZD7P\nM5dTVzpxsU4F/NBSHnvbRF22G3dw8edI5/4AreG424vxaRrEz00/iVfw93fRFpDb4CyQV1UX4VNn\nTQq5jMpYC8rQ7qIyLavicNV51qeWilZhtQzsehpt6aAFZXEGnNdqoZBznu3i0r2lfRWyGmnTejVA\nQUCh8gK0egp9Tlzid2aqiJhFDeJtCgQzhJ1663VMu0izMSeafReX76ILAI6Zq7gy7QMAJIcF7JWY\nQXucMGOubRgrpwipZbYBzlHyr1Nc7bh2to7Dj3CTPjm2jEMWGm3L3j4MzfB445sZcQXrByHc/hih\nvEc8dWy8yXN4z8IyzvTyfsLRN+ngzVec0M8RNtzbP4+Mn45j+3oN/TaeRSvWuIn/aETfkDbJ9XW4\n8jRsqW7K0eM1FTTznO/fOSbx6QxLj57qrOHy5hcBAD0T3wAA+GytUCfIU7XLgJr8UwCAE0ffwbdf\n52b54CFmS3cXQyiUeA7a4q3g5G0WcEn3riEh8hR2qeko/Hj2AlwJnj3Hc61IneX/d+48CN1vHCWd\nd/je+wN+/GYD2s7e1wlvlZvo0kFChD/n0uNWKw2qb+ww/vI6+fLhoRXcXCevUx9j4Y6+N/zQp2hr\nNDuNiM1xE0/OfxiudhrzJRUdCefV+xGWsfBMwbwdtRnSvuLYitx/oZPyuIQbvqPVjvk6YfLJchVb\n9hH+3JgawsY22oLitz6PHZ5XGlDF4fO7YPRwDufmJNgup7OnGqFjVM9dxmaAZ/Y97r3YrNDRtaSW\n4bDTKcvJqU+OhBlTetrJgXgXKkuUSYmzH1EHnfpchnzYZ9nAzSnqwLAmgO4+bsLTt4YRNPJ83tdK\nPa7PZNDupB4HDUU4dHzHoqyO3FjjEqYAIJvvhMTL4MdaHoFaTT1tb6MNS0RLsBR49FXSz6JQ5mZo\nkOew1c0Nd87CI4+R5SK6s9SRhGcIfVHRdjFdQKhKRz4m2nT2lfIIhqnH6qFVZNLUya6WALQBATv3\niiJL/jTqKur3+qoCA22Uz4zahoy6cY7PvUYTam6O5miO5miO5ngfxwci4u35kLgDVswgNkbvza1Z\ngrFOz71oTaMe3AIAkG6lx5ePG6A5xEjPc74T0h5GSMH3RlHt5yG8ykOoz5Exwv4MPZJarQ+BecIX\nxZ5ZmFYZKW9fYjTbrohCLiCh6cIe7BXJXIUlI5Z89H5bE4xilcFuqCR8V8bb2ZC29UfpaXfNefGy\nhe89GLuOn18iVHeq9Vv4UI5e9yMKRuLrx3bAIhpwv9hTwmOb9CaPDZzBP8TIh7RBwLLOixi/xm43\nd259Grn7iR5U8iX0bGNkPvEm+fCLeA0fPUxvNHFpCTfqjAhmP3IM0NIDl56ilxcZfBkDO5k8NJn5\nc+DW3bRJI1ZkvIzGFZv0qJUmG+p6epOOgTzyfvp2nbJB5HoZBWij9CpblEqsiSL/BkcHFKv8v1Gj\nhUUUB4i4GJnKJb1wljj3COLQ6emFDksMiIq7rKYOPrcUnkOuzuhYlyyhp0RPeEWZgtHIyHFDlLrz\n6Bon6STkMphFYwLFLDNNS7l27D7EAg594eexrmRUXdXvgEIUEHHEyL+iI4yYgPecshV03OQaJ44t\n4u96KF/3d1LuA6Y6DJcYiXj3DMO2i1G1vSWJ1oWjAIBTZUYWpug8AqLLy8PvdOPacRacubVLC/dL\n9OZv/Dpl7ump5/CtBkhF+6EkignO0yeau5d8rXB3MILaa7LAZCc6sdMMSBcp7/EF8i7d3od8nlGj\n0udHQko4fOMHfXjuGUZGN15kFFd6UgrnDepxOHkMOx4h1Gyf+SquXSe8ackwwak7k4XsNwjrp19q\ngVTcm609oUbqmsjQXaG8fNPYOJlx26Ifc52USTWXGLesr+DmChumPDWUwo4eQqmpH4dwvEPcs10h\nrLgm70HpFnnygmwGz1SfAQCU01/DzEXK4oNKRl7nXeex9w6PLMLSIu7cYYTZ776DssbHuUsop0td\ns6i+RHRioCOOtUu0F5nFBGRTojTuyBlcL3gb0gUAU6YcjCXKwQ5HP5J1IjzSgpAN/RD6RLGYsmsM\nUiNha7tkBJ4u6si8aPpulShgdHEN85lNGMzcCmTt3egvMMo0lHn8FI5qMCpuJyzoLNCGqOux3gqG\n5USbMpe4VsPblUjcIHrTnq4hLBoqFIsVZAfv3QBi1XgF/SD6kpBcgK5AWasv0sZ32wfhz1MOTeoK\nqmratMGP2hC+xmO+nivUp/XtJXSBfHQX01jKETLP92ygPyY61vXS3l9a8cA8yHVVqE3QFfnc6uo+\naNpJUznOOQzAiaui81p3qxzzgWUAQLCqwpOlxo1k7jWaEW9zNEdzNEdzNMf7OD4QEa9kjckMOWsO\n7Z30asyZPiyllwEAHW3bUZXTE7Yu83C8ro+je/IoAECnzKFiote3uC2E41foCd45wCSIuO0Wehnc\nYTyRh91Ir2c6osKClizYJ6FHaNZsQ3mOnr9jyxikKT5jZ+42akGRgKCiR201xLBYoO+iKc02pK3/\nGs+Oe4Mq3LCxutGl8B9D286z2ofnP4E7NXGW4qSHuTxegucgI/+HbtWwdJDPTv92HruUPL96t8T3\nevZlcDXHSHnbZ92ol68BANwvRhFp4zwTM6I6T/caCn9Brxv/Wo5k9BcAAI+fW0A6Qw+8O0ze5X9z\nGPUxesRVY+MrNzXNOqpperdRDT3BULQCnYmfr1SqSHr5DI9GAt06PVOf6K065atiOMToLx9PIFcg\nbc5CHFkfozpVhp62plBEWNyrs1ZriAT5PZmijLCSXrU8STmyOXXoTTPazBVLiFt5/mzYrCIS4Hrr\n6gJlQePC7ZH223gqzjn8qMBIW7a/joCOXrCr3o1xA1GJ/nwA6SLPKcuqZc6lfzd6/v1/BQAYnzuB\nTb2YW8GPFtGjObmLc7AkW/HUr5Hvobe+hl3tLBD/7coy9FUmeBVExOvuC+NTorToO590oD9Fnnas\nuzAvmnjcN8NnJXKNGwlc7tBhrUA0ZCjK6G516U0kOn8DANArfwvvFXhnvftMAO8NU2YeijJiMR5S\n4ZKUsir5WytGvLz3Omf/McopRt2u7eSN4b0lyAxEH8Ym/wTBHkaQ90XksDoZxcprPF899Ys5DEwR\n0YLiGHa7GbHdrnwD7iijwmgr+TAnrp78j8Oc7kJXO/VhPM3PTn7vMXQPMaoZ+6Eaj/wG4Zu/qclw\nrUz97n2L8lS3lWA4TMRg6HUPViTs9bqtCoS4xJgaZ79kn6ULS0Ehk+4oArs5p7UpL3yjRG9uJyjr\nW7+px6y4CnWl3onnovxepXsW/87CvsG/Kn8FVhxoSBcAJNeM8A1Rftdsy6iNU7dsu2ljML2J2y2k\nua9ugzdEnSxt2URQxci810y7UQy0wrsqqsN1uTAoIQoQS2/iUpAypfZQ7l06CeCh3Es2O1FdpU52\nWNUItBJWMOzkezezOuRGOR9JvQ3xIs+900oJ6vPJe9LWa+iBQvQitil8sJuXAQB+BRPPyioDzC2U\nk8HFPmRGuBgrN9TQiB6C+j6+dyVZR0DGiNnbOYURM/kwU4tB2kLdmLhJZNCVS0C2hXpSWu1Hpk57\nNuhQYllD/kqj4kqZYhItV4hgrPekUfYxqjYmlvFKgOv8uXtS+P8cH4iNd3qKC+zR51FoJXSRz/th\nVosSgqkcZkUtzPYKGdcSLkHp5qF5YXsG0pIPADCoViGzlcyxr1CZqhIHptQkNa2MQzVFo/yg14qN\nCgVO18uNbjEwj3Y7DUXPjRimrRROh9GJqpUKObsqOp2U62gRmaSlgcas3HmE0M9SPo7YOSrmwtY/\nxTMJwheXLuzBlie/CgC41k+D+9Ovz2OYaA+Uu+X47Fka2tkBO64+yQzG7S28Eyx/+w1k9tNImoNv\nY22OF9qN7gj83RTII+M0guW9Xrxzhwlcg2NHcTtJ4Ry+bxz1PBXnH4qEGLdfOQhPOwX2YtAJ4PRd\ntCnqcqjF/WUNyNPEQBUdciZ4VGL74Sjx75VSGYVOURylJpI6EnpIlOK+Z1YDs4abU9QqhUsIcrEi\nevTqCtCE+D2lrYKtLvLEn4nAWxeZyqKEqEGih1T0UTU4NXDVRRarTI5torDDYkI07q40vn/3QN2O\nS73kSUlL5T+ayuO1CUKSNxcG4TtAh2b+cgfqYsEeO3cUAKCeu4A/e4qJUT/X3Y6Kkfeka5rDiJVo\nuErvMKvZathAXfQPjk634Os7OHf/j7bjORk3u9pRGurkrAl/KqA8L1bQpuUc0kdHsXWVtLzbTah6\nSD7dkLZHww6Ek9zgxocIwS5W6nBc4IbUts2IW/fxHQ9dlaLzzmsAgJeOU466dBbYs3TaUgcnoH2b\n672takTPI3SMzy9R9xZju9Fm4CY9eqgG6WvU2XBpJyyLNLRTItlRdWsHdojOYZLqHYR0dHT17/0l\n2maY6PeaR5SOfFEJ4O27aJuWRfBukhvHCQX1NWcLQqqmUX65bxoTf0sHb2AwjR4HdWRjinOIbEZh\nEsV6Ev1yTJZ5zBD3D2PLDW6cr3Wz61fuvQSOa/j/zQkX5tYoLx/5vAcXxJ30rknSm6pYEJSwMM/6\n0BzKIDxflQzjd8wigeuNElacmbto+tmIDvqRTIie4DILqr1co0RU9JiV2vFIOxPkQs7rCEZImy8x\njxqO8hmih3mtlEK/2IRW6+vI17kWa8oSHKI0o0k4eLYVHSTZ3QCAQm4KblFicWlNBW+JdO6w0TF6\nZ7MEk6jVXtGGsVTm5rTFb0JpsLEjCADS2Rg0rZSv9ZYwIiI73qCgzcjqyuhxUB4WklroypT1lqoO\nNhVpqm7wWNDo2Q9LnnpaKw5CHiJPPVU3FAL69vnoMAQTQzCmRFSmV0Epp/0byyngWeUcVDkGfWXT\nblQPcPPXXRyGQUJ6YuZOaByNg5N70vsv+nRzNEdzNEdzNEdz/C+ND0TE264XVUSkLiTXGYGuaHtx\nuEgvtXpwEbsk9CgkMnqzUW0ZORs9vscVRby7yYhALW3BvI2eSNc2Roct/m5U7Ez2UNY9GBRR7HLA\ngwEpPaDsHJ+/39CBpRQ9pLJDg0G3iORmfTAYCctZKvSQxiRq9NeFx3upoyFtmyZCLV0HrTDGCANf\nWJYjoOOBv/+T3fC8zqSrZ0+Q9vs/5cNPivSO646TmHqBnpdFkcXcN0jzqJ7PPdf3JHoXvk8a8ocw\nkyMfHnHvwcYy59D7BUYyL4114OjnGVlZbo2jU06+fzFYwNBbhF5+qZv0eK7cwuu/QBjWo250cQNQ\nl5NoLTGK13kIl5cKIaiUvL6UVGRgFX1x7dEuVEXv3nwrPfFaxYeayLcoGFLQiALuOpjgr9IjtbSQ\n54aEHFASLgyVTVCJO9XaohVJHT3deIJ8kkuXISnwWRWpCeEZ8tXWUkUkxheqNYycSsuNO/gYdMCs\nuHbilNG7nnUo4V0gnyQ9boyfpN9qvm8J+jJh0T/8DZYNPHJqKz5m5P9NmybMuXhNxrsRgn8X5XPA\nRzl8z5FH4Sq9+aFdBuQv8L2jo6/Cn2fFpkHRxWl2+jp6OonOXNOk4BPwuvNH86j9KlGh3/QTOflH\n0/ca0jZh38BsgfwtKXiM8cQWP4prjNDf8OyCXjQamPuFUbhfI4pSGf99AECg24cZN9GQT5csKBzj\nVTrFjysohsjf5XdYblMt3Y2tfq7bd+87BMs+cZ0rMYNNE9dozcPkwK3v3sS7neTDne4j+JKe0c7F\nK3lMuc4AALo6PwsAeKA2AZy8mzb54gXsS7K8YaybkVtu7xB2SSifJ+wbmO8jHF5aNWMqziL/3zAz\nUv+TYggzfh47OYoFHBIoS1axiNP6pzl3B/k6JPt5REW1ueCwCx9q4RHW5W+fQV31JABApyY/Ctkp\n7BLXnPaqO/GVBR5nPWJex62zlOWdO3dDpa3dTZQYex1GzINHDzsLP4+0glFdIsR1668sIZcnoqUp\nd8NmppzlF71QtNLOdWlpNyYsHlzW8F3xhA173MIuaCqIqETi2pq4b6/VYtVAG/JozoHnDYR5T0jX\noNxFOTg5TpRF5nJA7iffb2oHMWxlhGjxXcDMRuNERgAIGcrI6QW0u15DsYV2w1ih3Pf4Tdjopl1W\n6zag7efeUNKrkV+i3OvbiUi0RC/B30k0yTBXRq+4+ras96M3yPkq+yhbCyFgt47v6vLuRGWOFONr\n6gAAIABJREFU81Vo5ZA6iaSpTfyONJ3ArOhedKAthPk66VRtqGA037uPcqPxgdh4e9t5zmKMT6Oe\nowKo88vIDlMADC29qN7ieZvRy41hzdwGWZQCe10Tg9ROmMKcUEAZoEAlBc6fnt1E2zZCIZpaClkp\nDYHNFkYtT2VIDYt7Xwse9O3gAq6sdEN2g/V4J9qq8IoFzMwRgpFBhnAXYZdk752GtE29JrpslPb+\nd1jz1xQT+Csb4eFPqb6O6U//ewDAS3MsoKHuPA73TwhRTbvisO2j0N9p/UP0LFDANaKh+O5dXpij\nzJCuvz2No3oK3Nf7XkDH5hcAAIvP81kDxjxy73JDnz+hQPsdQmbP9C5gcoTZr7EaawJP7+jG3CHy\nJPPaaw1p05rVKBjI62yMfDApTYjoqPC7VQ4shUT5TnUOMatoociPoqKMoCTOPjtULoSXaKS0m3VU\nu6mE9RLXWKEPwpClAhTkcrhqXO+itAhDmJuhUks67TkNFFYqU0iZhNbEZ0UXEihIuXbyJDdjVb1x\ndqxvwYT3+miAe971AQBStlXU93DynZmvIL2dTc6laRU22kjzwQL5r3riBmrnaeDXL70Mzw5mwkrN\n16G8Qr7ftHDDsk+2Y9pA2oNlNY5v49yvRr4ApZlFImp5Qn3LHh1Mewm7PrDwIC7LuUbd9XeRPMvO\nPXLtNwEAHvt+QECa//dhzkkxHKLcT3i5EU5+eQt2i6IPxxbmcdtDPlXOyzAfpTHXfuxXAACP3ByD\n9TR5s3z4BmR5tvpbMl3F0df5944DhOc7cz6k4+TxfsNpSPPcFK+XFvGAKJuYW6JOFwwPQeL4LgDg\nt6vXcDJGQ2tWtiPYwqzw0AY3G39f44I1j+54GmenmeltslDHLqym8UpJlNxUWTGSYzGORFc/FHXe\nEvg1B7+zOiZDqUi7Ec4OoVXF7NdriSWMqsn38wXeUZYnXkVMQyi19lYerzxO+1B/3ouOITrZ4300\n1EnLJkaLtAWazQ08Gye8nOvYCZ8oHFOUrqIeanw7AgBm9Vqo5mkrSy1F6DopM8MxbhYJdTcwSJNu\nKkthj1NHRu5XYL3Gd1dOc8NydRRgylEvVvQxJMdpH0vGZbRV6DA6JULHLDMYldNxDPevohd0MErb\nZFgKiDuuCh4J2XVRVMVZrju1DGOC9nyykkXJfu8CGhm1HRC2xC7JQBElHzpVtJk3DOvo8Yl2rzIJ\nIkukc+eWPApWOlVBUT/AY1NiKCC6BWl6UBA1Bp5U1DBTpLNbWmfBpcd8KcjrhOcDihisou7AzpoU\nyzkeVUjF/eN6ZxL7k8KeW5KIyihT9g0VYqX0PWlrNJpQc3M0R3M0R3M0x/s4PhAR7/QlQre6A3Xs\niNIrWh9KwCaSbdTBLOZk9JotUiZfOZIrkHTSA3IVtuKWhJ5pdyWPqkU0tZ9jpBjP/hyMCUYGgXIW\nClGtKjlQgSFOiKVlhV7ndMWPWpZRTa/nBkJb6WlXZkKI5PgORRt/ehVjSEoIq6qU2Ya07X2SkUrx\nrXH8xMuo/WVNH5znOcfb7mOQ+ugdr7xN2pwPLmLnACNotW4P1KLzjeS/PI+DHyfNIxPk2aTxbQQ8\njFI7ZO+htOV3+Yx/mICxi5WM6p9hwkD8nzJIGb8FANi64MPgDKO0OecGqlJmrr57hp5b55cG8Mh3\nGZ04akH8uAFtsmonQqJ6TruckWlE4kS3nIhCwRCFTcX1TOlMyILesVcUUc9Ajc47hHrjnixaFPRc\ns/YEagpCTBsVJggNVL3Qu8kzXWUNkapoPG+eRq5GL9VRose7KasATkLutYAKtTTh6jFzEl6VuK8o\nSkUq5I3X7XYP4D3FyOfGg3y+OROAU8uo/S3zJ2HIiAbamQKis1yXflE6VLkxj9MComp/soTkTxkt\ntdyXQWTwJwCAtjCjhOjID2Ca/FUAgHSbEu0CIl5+ewNdv88Ew/E3eP914L4OmETEIR29DKno2DLQ\nfxCvm1gZ7YyesPe/yiw3pG1uLo6EnihBx2Uecxif/Wu8WROlVCsrMIUpD47hazgTo25kV6gXW4db\nUBAZztHh15B/T1QvUtgwv50y3Bvn+i1lXoZrlvKb9CkxtM4IvKN4FO9WCfNqttP/d5vfgypMOTo3\ndQSOQc7/tMWMQxQpDA1QdjzW0/izBrTN976NGSczg3/WpP5Y7wZOKzjHWMqD7f9EGVi9tQbrENfg\nzMGjAABL5zgeGWFE+8b8NeQtgu8LLbB2kaagjEcbrgUfbCtMDozt/Rskv8yExwd/QYLCEqO+zSkB\nbdpboVwjrP+KZjeeyTKCnM71weKmnSpfMUH6mLkBVRye+XEYRB/k9WoClitELaRd/NuWUB3FdUaK\nqf55BC2EoD1TGzAVuXZrx2hHhzd8SBnIa3kgDPUgIeiKdCcUa5zPyijlv+1yDWsO2rypK3I422nH\n4i4HdiaIMs3UuMbVmRRMOuqIoxaAH0LP5qsoTZ29J22OUBjw0vbYSm4YExcBANd9RCQcrq1ICtjf\nbNLCIxIHU5MqlEao6/3LXMvTJjU6RGMDrfQK8mpG3ZeKFShsTJwraLiGvf5uXBENJPRvG1E/wWct\nBxxQVvjuQDvRiZ4eOd6Lcb2dN2OQWYlw5G0W1DL37irVaHwgNt4RH3/eMDixquQCt2w4catCgs2K\nDlhFjeY7xjMAgB3RNixukvlLAS9GH6VQJ2fdEE1JUApRodtbfoA1iWDSrh6kb4pm22eN6PAS1rte\n5vM7gx0wKpgtua5WIyFKFxpkGhRkooarSjR0d7bi/Doz3kzjjaEv13XRNm+HAr//DoVe57ND4iCs\nckYtRzTIKxaDx0nPROYK/tnA86Rnx87jPSfP9FKfyKBfZDDOWP8AAKCU+lGfY9PssdQzkIszy1/e\nV8M3ti8DAEZf4CZurWkw+whhTsN4J/7qj2mYHj5twJ5rtGwTv8DzvKemZrDVw3Pxsc3JhrRFHIto\nDXC9Up3ktUMaRVAtzntTNpREk3OLNA2DQWyyYb5X7a5iRpSyK3evoX+Sn91Uq6EpMhO2P0cRlepX\nEM1xE0/q+2EMklc6kwJSGY1qTTTPNjs3UIrxXeGNNJROOlq7C3psiqIYYSl/6rSNIaJDxTjGdnFN\nsyEaX8OAF+5VKnHKb8Wghxt9BrfRISX91/dTRg5fzGFXlPIbUI9i/QtU7tE305BPciOvH6NxUNv7\nUNigsfPpgpgXRy+9o0soh0mbPsIjgl3mCL6vokH4ysURdGwXZVUv9WJHJ59na+NcNuYeBvCNu2hL\nt5rQUSDMneikczZj6sboOW68FakCiw9wLTSJVtj7Kas76+TVj06VEc8SmlVcG4FMOKS62mdwWhjM\nT4qiA6ujz8Cv+A4AoFaXovQwN3xT2o/8eToVWx4mT3PSVxFOE5I/MjyLbp24cpMtoftr1EPjLxM+\n/tprd2fZA8CZV/ZANUK5TaYpD+em+qAQWbD9V/R4e5ROQ9Z5FLLbdAQ+9TY3vPnBedxsI8/WLw4g\n+Vt0YvKqGbywzvl6Jwmn1zLdqB8ScrixDeJWFbCpx9QWyurOMepOyrAFm2VRj3ufDDPLdGqdgavY\nspUb6IWPZnBo4t4bbzHWBkOKsuPrVmHezg1QBm4mFypXsbvNBwColy9hOMMjqFlXB0IWwq1907Rz\n78Qm4OxlLeuC+g5s4kpe6/glFEdEjkaAAYEmrUU5Rzv2tLeIMbl4761zCGnp1ENK+yttc0BRFIUs\nTo9jvY32yjeUwYT6fkHJpbtoq/iyKIliI5pKK4IHaMSHpeRHWb6EdJ66JQ24YTNSZuYNFliuijLD\nPgZRmmQRVdGm1WEH5v2UX2ugAkOJm384exgAMG3cRFeQe8DUI0FsKXPuUWMS0QKfaxV2Z/26He1C\nx7QpFaZE/XVlIQlv3noXTf+z0YSam6M5mqM5mqM53sfxgYh4YxpxF+xOEiEDo4RVmRLDLnoRqXge\nEi0jIOc6oaxSbh0ON7238GAE66Kwht6yCnWeEErQQfhj2H4HuO4DAFQSFaSD9HjdKj+uefj3rmlG\nhRdQRIeBHl9MKkfXBCGEMX8f6l56fYHr/H7g4QjMK2RhUdm4HNpsjp5X9xtjeHEP4btC3oD6k/R+\nQ7eyWD1Or/v4l3lYbxzYi5SbGdlTyzlUiozY1ipt8L/Ov2cO0Ku3TErRkmOUUH12Aed/1sjB+lm4\nEizmLtnKDGpVawmVa+x8I7upxkdC9Fbt/VdQeYDJMEPj7LM6q1nAt23/DgDw8FNDwEt306ZK1xER\nzadHGHhhsV+D/iq98qKqjPaagPiqZVRyhLN0Bc7RkGiBUUEPUjPfi4pO3DEMqqEWCXDKdkau/pQS\nKodIuArfQb1E2K9STkIuoWca1tKPlGY0kKn5XqtmEBkR7YTjJtREUYBUgdGUJtV43SZHHkPlJmH0\n+LSIeoz9kE7wvme6YwmSOcpt9tcdcP0l5cCVFDT2JZC7QjjxWPvrODfDRKuXbTtReJjZkB93EhmI\nX3OjZ5Net+3JOyi8I3qY6o9ClSJNZZGlqe+zQPmPjI7/wfEOjr5AuY89WYddSfmRqOmJWw826qIM\nbI2qkRBrdMRL2kLmMGRG3kW2bvPAYeW6pMoRLIpjHvvbPgBAy8Y/4+BuZk5/J/AYjHpGz87W/4jR\nCKNm6SHqbt8bc7j9S4x0PjM1gIshRkZbUyU8qKae3kpzffZcOIzBNpENfWoUkaeJhniHQjD9EaOW\nWQ2jpUOtR/Hi987fRdtO7zJUDsrkSp40DrV8G+Gb7Orl+OQmLrzNuW31nUHiKOHUm6u0O9KDcWRv\nMVls1/i7GH9doBrWURzqZBR/dY0RauuW87jtYbJS9+lVOH+Zz5LNDcNpo93IiLKNNvMRPF+hLN9/\n+Xm0PcYkyeSkCzfOcZ579rRhxuS/i6afDZ0pB4co+FFcn4N6F3XAfIMInK3Nhcooo/z67Qewvsmj\npJSkgD1t5MlSguvqa4tjbo2y485bERL1Nct6A+I5Ro7tZiJtkofD6L5A6DxgSSMlusaVt7RBu067\naTQS4pasxaC2kz8x34PIW4mArKy1QBm79x3lVNALi16Usw3PQ7nEdxt6KSNzbRFoFkTxEEkMqbxA\nSXI5CBHGxE3ajGKfE4FpRuUx8zwyGtKm7YghEydylJbzXYPVAFYHuW4txVlc0xKRaY0lkB6mnfKd\nZRKgQllEYJbvrQ2qYZhlEq6pkEVE3rzH2xzN0RzN0RzN8YEdH4iINylh1JFrq6N1QZyhdccwtULv\nw+daRTxKj223gNILtSLWBTbvq6twzc//h5MK7N/CiFUyx8hhMWOEUc9oID7ngWc7o51MKIdqiFV3\n5iKi0L5MiVZRgL9ekGFyjZFG19ApbG7SSyrtoQfkzRWQHWXUHRtrnKTzoW6eTf1g8Tg+vMnPnNm1\nAZ+47iIJv4Liu0cBAKFDoq9sdR4P+emBD33Mhy99n3P8nR3D0D9Hzyo6Q+/uwupN5H+dySSpUyfQ\nauKZk3Hib7AuzrIS10mD7JGTeLSX77p8vxaPRBkpfjv+c3jiOKPJI+s8P4xujOEXj5D/75xsXN1J\nJZVCIaKWiJV0YrOEmI10yrUmxNJcA6PKgEBYnNkp6flWgiUofPQqpatBFKScr7QGVG2MfhMrjLaK\nmiwMS/TsIyUXLHnyJFZX/fcrYRVRhaxNbcRNOc9qpAgjk+E5m1elQ2yd/LMLmVMoG/fRDAcuwGjm\n+47v47qPRZ3QPkpe6JZbcF3JCCb6V8Nwn+DaGc7xb9Pu++DuJh8WXzdjaxfPB6N5DVpqfN6Na4xO\nvF0xTHyK8ue99ADGY+zx2lm6AgxS4H9xhp76D2ffwLH7efbcut6D6608f9KbHHg2Sz/6BVGO8HzO\n0JC21IM7EbtMvi+rGW0pT7XiVppyZJ74BtrfJkpSPtyGX9pkYtiGhrqZ+NQOfDPG9n5DmSvoz/NZ\nC5pO5ByMti9vkP/h7Q6o/5my/L9bbuCEk1FCMncCM2Gu8aqRMmsIWvGOjWvZ5gkgtMhnuex6XM/z\n904XaZOVjwL4D3fRVj5/DZcrRG9MuZ+Vw3wcLtEAwpl34OcXnifPThxE/A1G+a/pRR/WmAR2cZe2\nerwdg1KGU1HjFGQKRrEr3+XZqOTDNTx+g4mNa1t1MP+UKEDFcwGDfj43OEdUaUHxbRztpOzN7m6F\nX1wb2nXKjfW9jKTfVH8ID8tv3EXTz0ZRpkdEQlmutu1H/yrls9BBOuNaGUrnueZ1nx/BMqP1gUAK\nE7cpM9Yj5IN0VgafnjprNwDLm/xeJJuCWk36VWXKqbWUwoLoIa1X9WMwxYh4eUqBBQ3lb3eOMpus\nfBjzdYHK2WLYt0QbUlIHsOG7d5OEltIcLBqBAvaGMKgjH25mqZ8917NIuYj8tUhsKDh4Zi0PVbCQ\n4DYWNZKe7TO3EK5wXmGpC603KePeLb0Yr1Kf1AmiJWfbunF4VuR5eBVIn6KtzHSMoU+0RfSrKRsF\ntQq6G0ReozvcMPpo22bn07CnXPekrdH4QGy8RQ+NTlvBgHgvIVT1XC8GNBTIWd0w9FISfydIw6a1\ndiFp48YxOW9Ht6gJHI2s4K1b/KyjjwZ+aE6C+W6SWhifxqyERtBuDKBDVHCIVKlgNX0AKxvibmrH\nOegqFNiLxQq6MhQ+TZgKGJbfwm2l6PLS2rh27NoxJoMY/Bn8VCR97f7JXpTMfF9WkUCxQoHaU2Gx\nBM+ZPL7zMRqa6u3r2J2l8C6kY9AJiOQnj1Chh1+Zx4kk+WR9dgVfPk2BtPYP4MFHKciY499Ksn4E\nAlQ81zUHzitZNnBv50fRO0ElXohSaRb0BayfJCTapW/cRzMT90LppdIXRd/NqqyEDSl55gkuAqLe\nbnZCjhYv3xeQ0lkx6SOohAhbpXUSlENc23x7Hdk10cS7wvVJKiSQVuls2FVyLAqoWZvLQr5BnFvh\n4hymYmso52mgdUoV0nnCvHOSGVRKdNBMop9v0tm4rKIuswOZzVcBAO19hOysLVMwTdMRMMVfh7Xt\nrwAAm1vOwh0iH5IPUnYWVTporjIBSJUZQfgwDfHI1BC0K4Sob4SZxFft7kH7OOGw1vJuqFoJs23f\n50T0NiG+1TR/mvqfxiVRnvPA/tt4R5QpfDyxjvHn6DAGJvm3Nnl7Q9rWLqrxZJrzuSbqZ79aa8eg\nWySTrD2IokgiyZz+MWoDdBAW91Nvlsofwofeo/Gd7Ykgu+IDAHh/fTtCwqnofIk86+xawKkSs4RP\n/PRr6BAQdeHJG7CLRJaZOWbfJt0JHLPQ0L56xo6PfoEbfj3ajenH/hNp+r3/DADQRs41pC3/B0/D\n/uIPAADSIjcTb4cZFVFq9mRLGK4/+yQAoPrVOVwZFn1ka3Qgd9e3Iyayeg+fOAHNDd5hD0wbseqh\nnn7xs4S7b7Q8hGvHKXPz+U6Y9NwU75uO4M57hNcjH+E8+8KH4JFSDnfGryCgEh18vmjBwizpHHlb\nitJRRUO6ACBi20Axzw27LX4JayMig9kvapH7PSjouFa7JpWwm6gX4X0OOETZ2PhNOtYzg3fgneca\nh3MzMAj7qamGoJrgvdY50WvcuqUVhQSdutL6FQT1XK9oTwC2CfJtwkAbYVSexkacuqWMFHARnFtn\nuw5hf+NiNQAQk2dRukm5VbbaEciS171rlPWbh3Nwz/L3a75XMSLqJ8vnk8j0i3rwHVzv+YUyckFR\nWtOaRGy7CMoMUZiW6AzH7XRkWzbGsdEibhf4DXCJkrKmih1nRc1/t2IZAJCfTCPhFb3G15fQKjp8\nBfNGWPsaByf3Gk2ouTmaozmaozma430cH4iI1zNOj+RSmwcjckIB/oAJMQc9uvXiK/jIJL2LmINe\nPdQX4b0mmihsDcK0zv+X1WGMKOmV+AUscMG9F/IQfzeW1Dhk42cxI4NfTq8u0M6IpXNZhVWZ6GwT\n9UAgeWhbd0NupQcUEJWxVIZ96MkRMvabQw1p++o5XkXZ+cDjULqYnDV/8BVof4UenedRG/xqep5z\nx0WXnQdu4Ll/ptdZ9bTidwuMSi6fPAfNkccAAF+aZFKDv2crLsf4/12adfyhllFEzLKEtyfpje53\nCQ81uop47PMAgE/+0d/jmxN/Tv6e/ScslxhxuXqZALbjcguKO8gnQ6RxVBgPLkOpFRXF6qLpQCyN\nhOBpt1mKdIHJNGqTHNGAqABjovcd2FTB0Ea+hyJqZAzkpSWthVrApFGNuCJQsGA+L1L5u3UobpLO\nUiQGlU7cnY0yIs7WEoCZkJEkoodHdEMKrujRUiV6EFdwvSSbjZMiOiNr8G0wkWX8CKEoiUePgXl6\n2iv7R+AU5ffmN1pQK3DusZeYXGQfWkfU83ucY8dbcEwQnryv7w6WU08BAFSi0tZQ4VmsdDEyCiGA\n9jJh3nRsEzOv0jdWfZy0HS8WYdzG6k0WRT8+uck1hnYKi2/yHZ8bphxdiTZOZpFrLmPFSCRm8DVe\nJzrV8TAsDtLwTHEZP+pm5BkZr2OllRFFIk59HKqvYP9+Ji7KehcxFiAPff/ZgCuDjGoifWy+4Mm/\nDqefa3juiS2QR8mz/RMGzFQZfThFWUGZrA04+AoA4MBSBxammPSS2BPHh7/yvwEAao8SJZicuw/4\nyd20Oe9MoRgjyqLcyeh6RzqON/sZxdpOl7CSJJIz4N6P/THqsmYP6TVPWOGQUj7PvH0Ze4f/BAAg\n0X0F9Qxh8BmlkPlNB7JpVvV6Nq7FgJz26GTxfuzYxyj2nUWu5RatHmdFf+AOuw37xDHZO2Ud7u+g\nfn5rLYrP5DbuJkoMRUUOQ4HIx6y7D5op2k27lqhQSlGDOsM1P9mmh1dKWVSf1OJmmol2Fjsj/F2p\nIhZtywCArHsY0iCPALQLLig7qZN9AsKdhBZ1B6/yaCMJbFqJULZcqiHpJrq4sU45lNS08GwjT2sz\naaR1RKZ0m0HkrY2P4wCgZ5sHwXn+X2PPQxoij2erPD5yTZpQWKcc9kq8CDloY2zdepjvcD3jVs4x\nGZBB3klmn3/PgJYUeWrz9mIlSXvkAZGrW3YZtpaIErRKryLbKZo95BYxrKX9G88SOXJ1bCKdoHx3\n9XqwmqUNUYxWoL4xdE/aGg1JvV7/F33h/4shkUj+/59EczRHczRHczTH/8Ko1+v/r9Kbm1BzczRH\nczRHczTH+ziaG29zNEdzNEdzNMf7OJobb3M0R3M0R3M0x/s4mhtvczRHczRHczTH+zg+EFnNv/Uf\nmdWY73Cif5n3qEImPQwp3gVMShTw7OD9wMAkM/lS5TloCsxsXSnZIdfy/8qSFHYlM/9KIjN2wjSD\n1oyP7zC3QD/HLEu5MYn1Ht6bs0XJCotRj/IKz8dreh1yOWYBlhRRdLUxc7ecYxad1OFCh5RzCIXz\n+PK/HrmLtof/A+8lH+4Zw5uXmLFtTSbx4FMsS/fTzWX0iCL8V+3MmB24XkBsmdmb7d0d6Kgwu+5K\nWwkJHTP7XK8xq/nM4IM4eoD1HBPXOzAqMhUnQ/0I93Dunau8s9leOY6JfvYXdt4eRE5NPmzYZThg\nIM1x0e2mLluGVVwgvwEt3vw/H76Ltk8cA9odzPRcj5M3w0UTwlrRp1KpR3KOfC3vSOCgyDv4kYTr\n0h3Vwu7iZ5cmWxB1cS08+jSSZWaWb9My09ED4LtBfn9vqxWrbcycVJyNItPH+8EycX+4PpaDwcvs\n95rSj5tm5u7tCjqgZsIm4iZmRco23fjKqbuztj/22y/C6GM2YzrNu8ZeyQzSdcpZ3aQGQszkXJRI\nYK2KZg4y3vH2BM2YVDCz0mFwISHh96ReBYxz/D2SYyapu7ILEtFfdu32LHS9zEzd1A3AVl0mL4vM\nwsynjJAWhUyaZ1CTMtN+i0KLy2nSaUjSnza4jPjrL+67i7Yv/vCvkZ5mxqu8g3w05aRI9nJe5nEp\nPB6+788VZvyrCWbgl72UU9k5JRx7+K7L0QhcLcxyTSb7sC7ljYKUgc/SZrL4iJaf/WbMhANgYQTF\naglFGbN5JR2i2EE2jLSWPN+dXcGanbTVlFvguEOa9ApmqMc1eXzxD564i7Yv/d5NVPfyeYkrYi3c\nQDnCu5pzOgnkIlO+zW9Cxkb6o2HajGxBglbRVCOkVkELyoZLZkVJ9F+NzIjGKbszMNymzAbakmgP\n8B3n1G7s718mz15jMQ91zwzWdeyoZS0sYV5CWe5WDWB4g/yZ3Z2CQ08B/bdPbbuLtq9/45+hyDM7\nu2hxY8ZAW5BKiWzfVAWDdtqjsbkoLCbKZzJsg15GnVN4mIVcRxSmGD8rL1oRUPCz7fIZLK4zs9fS\nLXQkqcLKEOdo3FRCc4fva/NacNpIXre1sWyowd+NJRl59ri+DT8s0l63z07AfIS3BH7l0Y/eRdsr\nT/8J/izJLP9dm4cQP8HGLw+vsZnB865rODBJPfTcD7TPk57XNx5D8vD3+Q4H7793FaIIi7K++V4r\nolOiBGb+KM7s5O9Phd4EAOSsI5DLmNXs/vEw7mw/Q/7segsvnv4sAODDB5mJn7+xBR87yMzp33tj\nA7vErZsSLkFhdd5F0/9sNCPe5miO5miO5miO93F8ICLegoV32qTRCK7aeNdTMzOFsI+elb7kwPX3\n6JWUqvQU5eb9SNTofVQ009BkeK+w3l7GpqjktKbinSuXxIFqhaQ6DTkkBunNRw0utIcYleQZXKPm\nUkPTR2+9eqsCpajEU2+toSSnV1yrivuF9Xlky3yvPKNpSJtWXDsudgNb9fze/CkD3jzNaEe6dQYL\nY8LL76DHp3W+BEmW9yBDagP8WlaTOpmW4zkNvXHFRxgN7IzO4sYUvb/RzC5MloRnWryIPu0yAOAV\n7acAAFn/FXRNklBtZhEhcX8y7f8kxtt4182i5F1ZyYEi6tPk48HkYbzZgLZW0zHoNujxa+K8t6js\n2Q2TlRGboliCi04o1lVhjCt4V7JL9N11ywrI6si30d1pTDgYyRUKLgxO8S6q1U3+vxeh/0yBAAAg\nAElEQVTL4/AQI43FTBnuVVbgMrZ1INnHv8++w6o8nYdWUQxQpuY0JhwX90xTphLWo4xwWlL06rNb\n5cCpu2mzupKQjfv4WTO95HBKiZyRqEWmLsGWVkZAyRUlohr+3pvk/eEr2hb4+ihnwXAMLZV+wQgZ\nVHpxz9nIe5+r9RBqFfrAToMLq2D0sXepAHGdEUkNadSrNdBJGOGXci7IRBnTyz0S+LSipKaoomW0\nNq6CtDzZhp8Xxfv/LibkP72IFlHoXu3M4oVp3lH8gx12zDt5V3VxUlQL63JibEZUGdpzHZE10iEx\nXkBv+kkAQHWJiMyqtAffK3Hd+9NXYNtku8vQ41eRqpA415uMTHfYRhGTEfFaGrIDa5Tx6mIAd3y8\no7xPRz7UktqGtOnsG5i+Q/TAJOVn1sMSKK2kMwgFVCnyZcVQQ1uFz1OJXs8qfxZLKSJEvpoFKwbO\nMbw5BYuTuiPTsQJVYsyMhFOUJg3YECxSBj6rVGJmks+90s/Wer1SLbwV8iRuK2DPHO+TT428hKKO\nd+cRyWCo0rjaGADozRmc1xNR6IUJGKI9eugq5SGs9OJmjQhUpzEOe4n2M1hfRN3MSm6Xiyy12ptu\nR15DPjgVephEtT5/xwYqblZ12hRNC5RmKR68Rrs8NeAB+mmnYPVjwEqbFrpIXictGZg0RFnezWxi\nOEMbnE73YVHbek/aTtmBfSbesXXd34miiuiAf4rz8qoHoN9L25eZXsaElVXhAvfvhS1HnVT8+kkA\nwPovOVDR8a78+vhL2LmV65ab/SqOeLjOk6tE0vryM5gQbUw1A2egEE0vLr/4yzDuZRlMnCXK8pnh\nCv7NFUbt2p15GKKcQ939KOorjRuS3Gt8IDZeWZSGohpRoXCECuKMKxCL8O8JRxHqLJkn91EA1iPL\nkNepsDpzJxIG1t40Sb0IKakYrZtcSE3NhHiKm7RRpcZUVEBx6hWEiqKRfRchmHKgBIlR1I7u6YBW\n9CCNZh2wxjm3UpawimSlDrOfQpgf0TWkLXaRRvvO5WFs2DiHbl8V2hlucPU5NcpDFAa1niXeLkce\ngflpCoDyL2/jxKM04DmjFKlTVDZFgvWiHzJUsXWEsNR76tdQt5Mn6cIvQzvO5/U7SYO11YR9BdaW\nfdn6JioBKtg+/W2sX+KGrR6lQW554woiBm5Oq7JwQ9oc7WmsGgmv7VLSaM9Ul9BaIJ8yMh2MHXRM\nFKsHoB/ienpE6bdVeQ71Fm62ZtUwTGlCmREF0CP8mNW8gOQGKyhO848DEilUMtKRNNchDdD4DQ+K\ni/TxOqxaGuoWlwJXRUnJAdUK0iquU76LBqPX2LjXcDXXjVgb6ahAdH8xS5E1ie4vSSciy+SfXi6D\nSsECLbNWGj7t2iasRW7+CqkPJfcyAMAbbEXMJIp/LPKzLb4E6jludDFrHIo412JDWUVRPM+UpPJn\ncmFIhSOQkYyioCF/rNEU0mbqiGo3N6zS+GZD2rbOHMdPVYTn9nlFQ/u8B+Y+6suNlw3YKeDqqVdz\n2BQFOXR9pKcjkoLbQWMVGrPAFeN8V561InRalGCtUH73J9RYc9PJXC3aINfQQBXH7Ni9QJoXWlh8\nYKkTyNwkDZqNnUhYCPH1dA+idVIcixzhd4xrxYa0BfIVZFrpFBivUfYkjgX4xWnCTpcdBVBOVsKL\n2JRTjiKddDwPFpPQaahj62o32jf5PnXQhFkrHYyScPQKNy7DtMZCNyanH6ogN+mv186iM0nH2TnK\neSr0m7g5w3ekw/tx2E06O8YOQG+n7VGUVXgpe7shXQBQXNJB20lYPxQxoOsbtIWqbm5usoocaCPP\nsuNJaPtFUReZFNYKN719FR4xhF1J+GuErdVVGXIervfash0OFUti6mtcw2wyidfWhGNpjMIijvVK\nY0pk7NTJgCiUcR/mEUzREVCW+1Cy83f58e3YO/32PWnraLuEM2/RQdO519B/jjJ32fECAOCJWS3W\nvdxM/9aewL9to063L30L/ct0MBZ+Sj70/MSMPiP5e+3MEQR1L3MOhiNYu036tZnXAQDz2hI0S9Sh\nF6pT2LXJ/28xOwAF9WjmMI/Zvpt+E8M7uLfY7hQRyHNt57IVfMb3LwOPm1BzczRHczRHczTH+zg+\nEBHvgtIHABjQFlC/QUikqLJAmSNsN5Oagr2Pnr8yRi/DoVciL5KrJBMr8HgYOc0v2bHLSXgi42E0\nVkjY4XDSe1vMbmDYwWfkLXrkRFSgSRIKLKtSUJfoEdu1c5BuMCKuSiJQlfhclEUCEuow9pKFGn3j\nJgknPkkaeqYm8Cfv0btWXb+M6e2cQ06hwWCQsGlZw8LqFus8NAVGEaHhI1gM0l1/LDuP8x8nrLL+\nIuHI0EAYlgX+PnRkBKFvE6Ip75xBIiCSgrYzwWux8DBe/g5pmHj0KPrqhE0MhWVsOvm+ZBu97ylF\nEPeHiJPPaBvD6MVqCj068jjvptdpKbqg28o1zFcdMAQ4X5sji8oi0YGoUZRom9gJk4aeacS9DoeW\nULEzZUXgmIDdq+ST1dGCcIIeaLC3DfUKITNdYAHmJL1QSbvo+CS3IjPLyH9gdRS9+xjBrL1rx8gD\njCgq8/SOw+uNaZPGa5B5uPbRDKHHhVIS/VkRocvKyLXxCEBdqiMfJQJhN3MtawNFFDpEctvtLN6d\nZyQoa8tAJ4qrZ0T3Il1SjrSKqEarTIFOJZGBjMWBwiajN5WdEUc5aMdqneiCVplAXayNRF/Bco4R\nkK1InunL6oa0BZ46idoFrlvOInpe92xibZKft5hXUN3GJhwF+SpahHt+dYEynkkHIUlxjbUuO1It\nREZs/gcwWWb/VVMbEYVbySo649SRPe1V3MwwWvKlsnhTQti0XRztBBbL2NlK2TD0n8Hk5Y8AAC7k\nXoDbyeQVV+4gAGDFe7khbRq7HKXr5Fl5h+jOdSWMox7qyNnUCtJGytFWpRqpLiZ7FVdJw1ghDo2T\nMHDWH4GqLqLfLTLsXeIabIxTr1xtOzBlInJVzEtRFKVJY64R9IE0JcOM9gu3BuHo4XzskhQKWUbN\nUy0dgJGRsH7SBKvU1JAuAIhW1HBEaacsiSxuCPi8sClKsDpjME9T5hJmBVZbGb1lZqYg9VAuUwl+\nJxTfiZYcbcHaRhiOKGVxj8aKmGgwsK6nTkcOydFR/m/svWeUpEd2HXjTe+9deV/VVe0L3Q2g4TGe\nMyAHnBlyDIeiSC1XEqmzpLTcPYfa5XKPpMPV7pFEiSJFMyON4VgAg8EAGAzQQHvfXd1luqoyK7Oy\nstJ77/fHDeiInOy/OPhR8af7ZGV+X7yIFy/evfHiPa6Xu149ZraoZ+m5HEZ3+Dxrn7W/wyo3clYi\n/1OOBCRFPkO1cg7fLCgfKlv9P2mw/CJt0M6GBvuP8PzHFebRROjpGCpJpkr9XEWPaug/AAA67RzO\ndUkxD936JPurK2PnAe3Hcx/fweUS7cpHrHH83xrql/s0U+8+enEF/0YEzZ1Zeh6HumRWrn3Og9Af\ncx3emeTR0ExNAbeWY7PVjuCFHdqHW4/nsfE9yvzc7z1UxL/TPhQbr1VQE9t9LcYUNJ7hqgpaD6mv\nGUUD0ioXfbPMiS7ouigpSBs6RqO41uK5zojMhY0S6Syjl4YkNpzFVIWGQooqqioqgD81i5CZ1E2l\nxwFVq2tQbNKYhSpdyJ7lAuncs0JiIZ2otNAJmCk1cT9MpR9SDV4wty5xA1BnujgxwwW2WzfjMfVZ\nAMC8p4ofG7ixtq6TXlEc9qErcqCOefbxUlZEAd/5FGZs7AME5bnxRh2jL/Kz4WtdFBfYj2XfPKJL\nfMbLGzQqX/EGsfYkreippSmE1+hg3Box40SKNNDWd2hwHx//NdyZoVOi67YGylbSzWI9QcfCY+R5\n0ZA5B4jzqyFjC71hbpDdDR8cLsq8r+MiX/yVNh6sirzXChekCho0t2sfFY0w8lXShdK9CsaOcnzy\ntwpwygQlvqBEPExDu36FxvnoYRlaXhqHivY2im3SzkpfDq0HjJKsGzhvkyXrQNmKziqsPRobOVUS\n6YmjSHeEI5DPQ1HgxtHt7SFn5+JcVFL23EYRIT0Xv1Q1Dr+ORjDn7cEpF+eUdzgX6dk+RiBK2Mld\nkAkHQy11QiVKEio2Scf2ehVoPNzwh/aHEJRxvqu1ECZ0nAt7grLHDtUGyqbNVzBxlIfv79wgrShf\nU2Fqgk5QsNxFL8sNp3hfAk9QlGP7LI23Wu1FVcux7ns6qDUEj5tro6bhfD4qo7ErPh4HNvisPCrw\nt2hy+uNVpG00tA1RynJk7DF0Nqmrpe9koPws1/qp+0vopWgQlRXqtME5uGLW7WIANpmoZLbPM7oR\njwxXs9SnkkWGQ6Ik5I6hBm2QFOlEmbYm6wpAI+Y9Ziihn6WtsMuceM9H2cxarou4VorMLepsbaaH\nqpR/HzXKke7x9oBBLqpz1XNISDnvI+UySh5hg4KX0dVRTrdUi0hucF50AFCEVlHrco5rdTfUOtoT\nxyidqHjQCGgoe1Mig3+PTma49CiKbp41W6vUQ/2DMC5IKPvYYxrIxYb9s7QBmWWuz2PCpM007cg2\nxVrYWkFPTn2QBDtY9bM/C/ucS6c+DXeVR1uevhY3stx4N2VtPOKk/N8aIFvht6yopwk8hv+Xr2Hp\njS8CAP6ti9ElSxvHMfYVApc97z5+8Lukh/+nM32kRymHKkgbf7SXwK2PknK//s1/Dukv/iUA4I8j\nJ/Hst3m0lBVVpRLdZRxf5iaevqrGD1Ucy/L1fehOEJj8QZx51F/yPYcjTdrdv/zp5/HMl85RtmwO\nyuXeAKke3g6o5oN20A7aQTtoB+0DbB8KxKtL0FvSOg2It4lq3AZAJoKc0BiCJE0PZ8dG77nTUMFm\nYPeNxTnYXERWBq0CCTXpVm2aKMQi6yDpIr0ns8rRplOIlDGDcl/QfT4GUaR2S0h4iVp0AR20W/RG\n280cltQ8/L9vpWcVkwGdEt3CkGJnoGydNtHx9el11KX0BOXTU9gI/xgAkHQ9DuMsEVt1n7SXLPUk\n5vJEaRd2UvjiEr39/3p0FX0R2FBaJQp+/Etq5Dx8xzs7S/BMU+bcvRDMAk3+6iqRjPppJSQiYvHm\nzQ4OF+mVl8IjkE1xzLy/yPG9eeH/gLFOD9QV2Bsom7zcw7KIgs5K6M3miiZMOt8DAGzvfhln/JzD\nDcMmbDKirIk2P4uvZmAcoYcpd+jQCJKh6GECii0+76hXoKXAECI3Od+zvj0oatSTdrWDlo0oafgR\n9rPYScKep8w9yRPolOntu2briK3RW5/S87mx5mA6Vtv1ol4Q94NHyaws1JIwtOjh74/UoKsTnThk\n4yjvMWL1loZ6Zl1UYKHHOWwZOliQUE+yZTl2BJIYfYoUl7KsgjQxAgCoy9PwneF8+rb3sd/nWFWK\n1Lmep4K5Fsex4d6HrsI5bjsnkRRHEj0vP7MqB8smK0exFaHnPlWnHjnP5GEqiLvPPqATJFo+o3Nh\n67OcT12KQXzSegn7aiJ/l9wAV4m6k3TpsNijPjT6pII1ezvYrJBFqW4/isenqePnwzIcPsQxa99m\n0JIzexV7Ns6P45+a0Nkloss2mnhkmozKJTORmaK0NVA2dfA+pkR9VXeajES2sA7lJMdUZwjiQYx/\ndx7zQbrLY4qqjvogzxQxJGpM31D74csIZGQNYSlKlB9ViWLqvQqGj9J2qYJp+Au0AXvNRdTFu82L\nRHyhkgIBOW1MpwO4TESQEbUSrTJl2stXYDuiHygXAOTn7DCKu+Mm5Q5OOjjPCRdtgjGcQFcwCmp/\nEbIe52vy0HtQXOZ3UlpircsaA+b6pMb96/PQusii6CfSMJ6jDm9+nMzL+NoaGjXSqs22HmkzUX7T\n9ArGa7SVGx2xjk0tjAh28kqjitRtou6poWnY5N2HyrbSegedHt8h/RcL2HbS3v+jJqPk31yoo/sW\n1/TefRkCc3yf3/A1GN8mxayXivvbsi4mNznfq2YZdJmnAQC/EL4H24tkjmIiSA3qDfzKv6bOfv/T\nHri2OSbfTJzDhIS5FhSLnPePlxN4q8ox//1fvoB394mIla42Xl7hPvEnD5Xw77YPxcarEYZirbsN\nS4+T3thvwiKMXEttRm+CCjMpqmZJpePY7JLyMTskaKSpvOW2EdNdKni0xQWiHZLDoOA7dnMl6OUc\nyDKU6Ar6Q5LhpA9LEuhWqCB72QJ8EvZBbfNjfZdKZCjyPG9X1scjKhrPze3BdKwJvGaTHjsM11/S\neJq692H+Zb7vSnoHp7a4ceTOsuh26+Uugs+SYrFFPoXCBDfT598OomR8BgDwhI5RfYVWEsd+wKi7\nLftdNEHZ4lMyWHdpFNaepqF+opGEs09Kflz+11hX0ZGYG6sheoWylT/G35dGT6MiNjqncfA1ANW4\nCpYGHZdMnwuho9uCrkpKyG0LYjvDxeA+MolglIZpdob9Mq91sKDjBvpO0ADDSdLy1m/boX2MG472\nhthwXEX05jjG1rUq7ozz8yNWI3J7fK5RlPryayexskOatzK0g20lackhzX3AS6PREjrQmt4eKFuj\nl4dKXLUx+8S5TmwGDisXvzHjxO4oZWvWgN5xnr2NB0nH5nPzyFtozLSHnsDuFRFtruthREXDpC2J\ns7JeBt1h6sA89NgP0oHYLUkgE/bB2eF7Qwo19uQch1odGEnTi8xKbdAZaOwLHo5d7tZg+ut+7CwC\nWZ49VgLULYPfgf4a5TEe1+Aa1R59cxhoU2fKd3hua9HGcFKUeLvZLMO9x413wnsfPinX6U071/Gc\nyop6hO8oPXkDOyFS2xmHH928uBrn4phpTo2jfp5jsvXNKPoTdEjHDHWcz3IOcIOGsfn4YLLOrcrj\nUo63B6oecbVOYcNoQ+hD+zBGS1yT9/IKGH38LkKkYFvjeeSKtAlDhSaky3S+TJXT2Fjmu4fepgPd\nMMQgrXCDqMfUiM/z3NDjiiErCq0nC5zA3KQMmgLHdznVx9pNcX+xdgRmK2MI9owjMOLhpfMkyQ72\nq9wkNiVOjBu5ufRuU7eaCj2cVXHFbXMcHZEIKHroKI66aCuTderE5F4G7pMc/930HbT26YC0Wluw\nqjm2gdvs7568AgPofLaLKexPcawMsidQ3iqJced6vLPRwjE9naSCywGVQ1xpslThjNofKtvJ7eew\n0+Zxl0LlwdcFuLGp+a9fsoNMlWvsKddR2Le5xQWPnIJjlGe8t4aoh85oGvefptOr6r6Gz7hpr3+8\n20fGRCf85BbPj+LNDP7br36e70qGMXaCc/vJ5h9jrMKI6h+8ymMT2ZAVNVFiMGgroBHgEd/cuS/i\nycXSQ2Ub1A6o5oN20A7aQTtoB+0DbB8KxCtpiLRidQ10bqKXNZcUvR36BbWhKFSiKLNDT1pqrdlA\nPyGiQydTMNt4Cb1lqKKZoafsGRF0jq0LU4ZoyN2ZQUNLb0dWBpZk9OZjE/QE9+JWjNSIKMY7NfRE\n8FW9Z4RZQ49fUqWHOto34T6dTYxMDQ5kGdPT85Kv6pAzCFr7MQvM36Jn+txwC6E6PWlpkh6oxuhE\nNUvvsO2uon2b94Y7x1/Avo59k4dEesXgP0S0yZSR2/ZhjIu8AhHdPD5fI7IatrwOALjU8CG3w/ub\n+qgNdR3l2M71MPM5pnGrvsK7tG87TuOTM/To4srBgWPe80Vkx4lEJFoGas3KnoRZR3Rhru9hsv0o\nAODc/To8T9KDVubJKBi9cty5Q4+2fzIHu/C6tc9KkGnTs9yY45j51xywakQKPKccj7WIJhPr8yik\niAKW1JT39YoF/eL7aKkD6UVSmtLZBaQSfJ9RUJUO3eD713JJF5jlHBR3OKg+Wx4tDWVodHSYbVM/\ntUMtFG7zO7YeveOGoQ+tnlRU43IW1nFCSElOgwcSetUulyj8XfYiKxXQ1qBEoMqAnL16AeNq6mpE\nP8J3NVOQ1YleTDYrMkJX/YYqNsNEeJYK0VTd6h0o2yd3E+g/Rqr4Xcc/AACMvHQTxYxIZXlkDPMr\n4q61RQZ5kcxR1cE5OWnu40KL62k5L8fucREYNnEPtyPsp07F8QjtdmF5hEglcEmPU8PUB9lqCPZp\nLp7XGnz+6fNSWCxcYypXCH0jjzoutSJ4RhRnj00IXS8OZmHK2h14rE/wHS2OQ8dcRr1K5NWSX4PM\nT7ajGqpiSgT07cuoF8muH/4CaWf7VB71Bsck1t+BTCTv2REMiF4hB/ZJtap/WQXvLtdLLqJHcpTr\nQVEizW6qvYW0TRydVd1QOmjH+mtrqOU4VnblCoq1h5dzletqmMqKFJRGBbRush2RFOe97dtA8SJ1\nx2u+gRtzRIA2qwx9A22h5wqR2WpgFto7jBwOj0xAdpxzK/uuF/We6M8cbRRkPnR6XEMavR/SBtdW\nIi6D1iQin21kW4yNe7gqAh+tuzWMCFRYyHmxOX7tobJ9c/pdvLB7gmMyPoV/vsd3lyW0y9WzXvT3\nyNzdDK1j3Em72s+v47KZAZhP3ORcaocaKLxDm6pqq/G307QP19yH0OtRZol4VnfWC1s0DABonphG\n6Q5lW0v9CBkj17f6pAheNXtQFXf6I298CiYb13H3ybcxGfU9VLZB7QDxHrSDdtAO2kE7aB9g+1Ag\n3qwIHNnX1KFUElEEMASViaimf30InQkik2CXCMArCaJ7lGcq1pQcRhe951LYjcYUPbZYiShjWaJF\nqkdEoRlOQa2lR5u8oUW6IgJ64vRsJ40thPv8/YIqh25Z5OyT3EZbxYN5aPmZpFWA8ymi7kzFMVC2\nbx2ibMqNS3AfpvfrLxaQFIEGDc0ZmCbZt+w0rz+o12+hEKdH39ZqcUv+qwCAk6lLkIogh7aSXuX6\njT/C3l/Ss525N4dkjs/6VDeIv5jhd5fCRHfy7jieGSVaujn8VRyp/xcAwFbNiOL2qwCARds/pjz7\n5xAzUj1izdxA2TYPe6Fd5/PcGr43tjj/31PRKUJudKT04NvPSCAL8/O2lbJrpDYsjNETv5boYsNL\nz/SkzIGKi/PteodoSGk2oBcQCfY7w9jKEVEUVWEojtIrXhH3jo9rcig52a/gNQdMOqaw61WLkE3x\n3bUi78LqU0YAb/+cbK24ElWRCaouzvEC5i4kNXrE+yovbOv8+77WDIOT81UV93h1kiIqIlhE4vDD\nLmV/azoplg1ETOUGz+hyrWvQCARXbDsxJtiDuMeBaIkoPmAiUkmgjqgolHFMlkG1S+S0nU/AqeV5\n5IOquM6Fys/JBQCtpzt4PcQ+fLb9pwCA60efgLPAc9+9SBhHGkSFO/e8cAf47oaZY1fCMNI9ca/2\nyNuYi3C9nL/2EVgXibLnexyHWKoJjDC7k3oxjjeSIpn+4iHoSgwGe2afZ9q3XcfRLr4LAJg4LEP+\nAlHuryvqeP02mZj40wyk8dwdKBq0FQNqu8QT9THKWLDrERBX8iz5GnbnqC/ThQr6fa7fbo93RO3V\nRWycpt6bdqyoixiOsTzQV4mMTRaeQ6s9p6Dz8Pw6saZHy89xuNeT49Ea9bei4roISs/iyVuU4Wej\nVYwqiH6DHTd8BcakOBYN0N/n+P10gGylRgEK0M55Rm3IbBNl2h20iaWNWUhyXGPnpI/j8C5RX3mu\nhlfcRMWLx4mYFfF7qB1nH50vS2FwkqmZ0sWwMkK2I2Zk3/fumiBT0HY9b9Qil+M5vWrbhsxT1Lmx\nBu3RrvcQbBtce/3mFkKNEc6FZgPuSn+AVGxf2DuO5hnq17lX/19Yfv1fAADm/iV1IOGvwn6VejJp\n3MaWhcyJ3azAyRTl/NG7nB/PeB+/5OZ6eulIAisZkdY34IFZ2OnqWJhjEzEg8BgDuHa1b2Nlgrr+\n8YwM1Xmuz6uXuP4Tu1KcOcwrkc7fvYLieaJf7c1NrKgfLtug9qHYeG3gRNVMevglPLjP1PtQSSi4\nX9JDw8QJKFZozDR9OxIyKojcVoQuR1pv1FyDQUTV9SUcmL22HRolaYhVhRqWKCdoeEKDnRjpyyGR\nSCC9I0FAwQ2gmtCjLqJRW+oaJClSg32NyCEr1aKwykmfWhxM6y2+JoIv3M+jKarSvOZ6gCkVg8HS\nvm+jfZlKL5WxD031azjyC3ye/PxxpIq8e6r5yRDOvEBnIitCsxd+41m0VmhIWsFvQqMT9LxyEss9\nGrZXpmmsnr2Sxb3O73JMH3sTO3e/DAC4IlfCZ6WxD7/1PQCA2qHBrkj9+PQzZwbman5kz4lKjIZA\n/zTHvy1ZgzIn7sYOe7Anjg5qd3xQGHiHTu6g4crV5bit4Rx59TK4alxMN9q3YQ5zbtNKLkbdghLa\nB4xOVDrfg6xC+jLnfhy2TeYSrg/T2N/OOtAXCVcUXSVaGkF3XbDDY2EQ2IMSn6s0ZwZIBnTLRjjN\nIkhJHFm0+lb0rYKy6+4gaebcKkIGFHu8B6otUl8MmjiGLCJy2lBEPcP+mmxdVBTUz3iNc9hz2tFz\ncL6HkkkUzPydtamGWaQ3TLZoJHtyH2bqXAvJ9RIMHcrmtnvQFnmkneIOdEs2OKr58q4KT/noeDS8\nHI/WhRUofpvG0/5KCVdmRvi5P4FUimM1P3QaAKDeSGHMzQ3U++1ZXPJyTZ6V30Z+kvp5t0kH+hmf\nHG/skt5TzPSwZKajULyshFQ4Yq3ZJwAADn0J0jzX3sXgEA6N09C+lk7D56Vhs3X5d+Ovq4C/+HnZ\nHLGj2HIxgEatZMBaINRCtc8NtOcGIhmO07hNhoaBG8fMLfZbs9zB+j0R4dyZhGaYc2w4bULkKh0e\n0yznOpGsIJvjevPHWpC7aOyPV/dQs1N3WjqOna2Rxt40NzJXaQoZEcA0faiO7Q2R9nM3/d9/N6iZ\nvBp0itSTpNQKv0o4tSKxj6KqRfYs7ZF1S4b4Ip2CrKcM3V3KFxT2tSw9jPEko9UvPtmDT0Rkv76o\ngUuskdwaf/NYO4QHFq7TTWUNESMBj6N0CX69OBZ5l07ecM+BTlDQvIdLOJygfTLfAu0AACAASURB\nVDin0aNVGqyPAKBwHkFJHHOpur+Klb+mjgeXGfQp7U4hqqU96tr82Ddw3ZruGNDPMmnL1DJtebJ7\nCjKlSL35lgGfGiOA+8H4XZhe4hw+EFH5dl8RedkfckxuPQXzOQbeXZ/6AmQiXbBijPtTrxTESox6\n+Gg0jW8c5vifzclR3559qGyD2gHVfNAO2kE7aAftoH2A7UOBePMT9JhdwQgaLaJJQ88HicguFFIp\noWjR+7WJu4kZhRPqPQYESEw+1JS8FiLNylDR0/touEidOXcNqEhEzcVWAVof0UO2KEFzWCSSF+nr\nxka7KPXE1aRqBgUxRIdUbmTFHeNGipRnReOBU3iHkfpg5BQR1S68zipsP6K33vqcB4UfkOL6pEyJ\nV4+LtH8hepijC49Auikq11j18KRI7cSX1eiX6a0HFolqNoMPMFflwf7K5KOwzzJr115qEtOiHvF8\nhf++5dvDIRANbKw9hUeUREvhUhgv/jn7+XUDvfLHLTbob5F2yZteGyjb6uwOzEfZj50d/t7k6mBY\nUJxr5h4aWUHlOzIYVRERyGv0ZquKNciygvpRHEerzP4cLvtRqZEerxnpoUa3NNCnSMmlNVqM6zlW\nbcld7I/yuoBUIMEhVwepbVKWffsSwnUG7IwtmrFaJ8oas9Ejru5YBspW9OQhbxOZGztEnapcBzkN\ndaeg6mKpTJ3RuuLoKClzLMXnmRQGNATdKHOaUVVRNolEjmqOMp1sUO/XKilo+pSt587BEqE/3JLs\noGATdT6b/Oy4JooHaaKivlOD6xn+3YcmWgmiutGeqBHrGszCjJf3cFXPv9kLnDf1lAeFKpGBwazD\nrkg7Oar3oiuuN+00RYGCdh72Xcq297F7GN9jf0Y+YsHGaxwrV4MorO4o4dj7Jaqu3UPURMTQ9dbQ\nPnESAKC5Rsp+UV7DOQ9p6V8eTePt63yGxzWLexbqcFNQiJ8PbQ6UbS+QRXWGtKjlCtdbPQB0wxxr\nU8GAE8Mcy8K2Ed0x6kxtkcdIt3r3YCxTZ6cCGtxWknmJ7E9iZJRHQVFxBDNhkmAmI4qLnJAidYOy\nb/vGsKTjXPSlHCe5JozUZeqL6XQN/vev1owXYZeJALmGA6X04NSzANB6sIJhE/seuRRAZo5635aS\nhTEtnkRjlShX2cqiJqHey4t16NTizvg45ZkubqMnsp6ZUg50Rqm/hVUrphepq42+SD/p8MEd5Rz3\nxiSwNDkOXcs0+rdEitAT/G5K7YBO1Dg3Joz4togV+0TpLFKZ6w+VzRa6hXqftv+FQ9eR3Oe1yXcC\npMbP3pjDsWvsQ+NPo3CEKeeN9hK2TaxjrtPRXt3bOI/kBOX8aLqEmrD3s1sTmDCz0MIFA1GuvJ/A\n7TefAABcDFRhWSeV/NGPx7GdEkdNCcr2VxUPftNP2Y61C5h463EAQH90BktHww+VbVD7UGy8laY4\nQxrSQy7OT6HKwZskddCWGZHPcWNTOmkQDPkqlE5BacqAop4DXbAOwfH+xXA7F5su9gBFKw31bMCA\n1H1xxtPbQ8rIBdAtsg+STAmaMbGJOOzwg4u3KJOiquX75HlBDVtSiMuo9COawRTReJHRgNq/MuLm\no6QuZt6QImJk5O+VsBXpKCmU5REqSBg1LA1TCSs37yBh2BVyLmC2QWdjUkvK6NJ8CNGfMKXZIeuv\nIfYG79Dmeq9CZ6TBU8cpz7MzDThEBZW27DJUGfa9kCzizScYUWwq8f7hBdstjI2xwkpVpEP8uRa2\nQ+Nhn7VdfkcR9aFQ5Gd5exOnXBz3mE4GZZzyK9V0gnJ7k1BMsm+q7S5qooh30LePUTvnec3EsVGU\nctBoRgAAiw0nCiKyNNvTQdMW90TzIjdvwQW/0I33JFVMhjnfEvdVTIqNPuUhbVr3/vz5LgBMDNtx\nN0fqeq4tUhtq9RiS8vfRdhqpNp294cIoWkOCEp8X1aySNui7dKjs9RgCJjptpWgPKRVp8H0DDZyi\n3Ydaz6WoT9TRMdGZy6vUmBRRtR0l/74lNaMqclh2Ox4su6lHwXwFdTv7mS2KSHpx5/Dvt7sqF+Y8\n1Hd9iZtpEx7Uv89+QdfHSTuN8vjtO3ipLiKYE+xv8sVFlF8R6URxGtZf4JHG/RUzAhLqquxj1AH1\npSmURY7d6Me9CGyRxt0utFB1cc22wHeterbgmOKavf+zi1CeZK7m9EsrmJimgyG9yv7eG8sOlC0b\nc6CrpHMp1AX9uBQNJ53TrFKCrkIcC/hKUCnFWm6IknRFBwJW6mGmV4ekzJ3D2wrBLuFxgbRPWjZp\ntSA3RKraXu7CIGMfR9s5JEuU7ViG/V2xVDFr4JjvbLex0xIR/qEU6iLO5L75IlRXH05Z9pVDuETT\nhkerJ5GT0Wnw5viOyIMw1ke5bj62soZ9F/VeXvbB7uLRglQkJfpu4hA+kqeeaR55Fb3z/PtooIN7\nd7j5OMZJE7ez1+EK8LO2NgKTyAleVz+A3sFB1t4lGOkcVSNVEjEKZgMe3eVYviO/jRPTJx4qW2Ux\njfC/53PnJJ9AUkVBX7jNsdadWEBIyY2w+5YJ1+I89nObvg01uPE2xrkuppafRkbkeGj2RnH5EMf3\nzmU9JP7/EwBw9AKf9bOvTMJ6nXP1ua4Xh8/ScY4ES/hnT/Hs9+1bvBXyNyU7ju4xZqfhPonmacp5\nfaWD5x3TD5VtUDugmg/aQTtoB+2gHbQPsH0oEK9WQi+4WVAi1qWnM7wbwX6VATshDWBJi6ToBlIi\nrVYdQ3JSdhV9HqUCKQllfR8VLT13W4leT31kFGNBerz7kigAvi+nHIMpTs8nvEfvUGOTQZ4litht\nm+De5bMynSLM4m5eW85/pWk/rD16U/npwYi3nSbC3H/WjJPT9OyDb96D7zhle9fwKkxORvCtiMos\nQ62fYGtV0E+udfy0QPpNZo7C1aZX97VvEOUVHnsRvzX7bwEAP81chtq3DADwRiToyYnILkgYAjr5\nshySR4jYnLdfhvUQv+tK3oPzJmkgrYLe88/qT8MXJ5LJOAariaYrwX5VJB1v0fueqLtxzUfUN1ay\noZsUiGHIiG09kchcjEi8E9iD7RZpnBuHUlg2kMbZq7cRlBKBn1klJbzvnIO0Trpsu6FGrs050pQe\nhTUlqNcO7yUnPNehEyjfWygiI+c7jEYV0iIyd1hE0mZLg6sTlQsGyFuCDmyE+V1/AfVN6o7ToUHR\nQ8bgZk+F8bKoSyqnni7J8ujbd0S/vAiJKi1BVQh1O4NaXCKDnjFjwW4tLsbPj7SNaNG9excVK8fB\n16S8fbkKCuEuZ6pVZKxE0g6zBOoaEUqtQdn61sE0+hFTFR6KhF0fx85a7KI4S33p2DSw/hnZptIL\ndriSfKHSR93RvFNCMckjCYWrA9n/x6h68+kINqc4t22IjEaaIGxJ/n21GsbuPhGtd+QBSuvUcb2o\nqz2r9GD3u0Qfy4Zfw/fvCSZjyIztLR63zFlHAAAJyWAaXVfaghZc01tprrFhnwslkfmrdL6CUYh6\nsY9Pot6jXcg0GSzW1/Wx5SabormwA6m4I6oaLcAh1rqiQxQ3atPhrkg/2XPmEdJRB0bmQugmGEkf\n65CN0u/r8do4x/oz0gqKAvn/VFrF7Cg/121OoG8dfDsCAAJuI4x7HFftoQgui/vgOXHcsF26h6l7\nXKup50chu0XK3ZyNQBJlP7Nt/n5Zdx3VPgOjRoNPo68XxRlURlieIXMyESYKTmn10NWprHGZGuoh\njuvYhhwxI8fSOE9qWJOTQrbA9bZ5NYeunMd9lvkA7vXOP1S2d38YQeMz1NsC9GiuiUxZI8yul5Df\nw9g250Jru4X7hxgENbH7Rcw1BFtZIEP30eQN/G/XqGcPPvY92K+Qdft0TovKSdrgt0b5XPXPgjAK\nRJzefxn7Dc6b92d7eOMs7cnRCin7H3bz6KW4dp1KH/Lqr3LIdC9h/8bgFKYPax+KjbdT53mm1lnH\nqEj/Z5MFsH+Sm9bhy0EkR7ghbzS5UOagR0jN8x5b2QZjkYarueTAoSCV+m6DA2ZONqFRkyazlu1o\nakQ1i1QcMXHv2dagATM7K6iLlJGj7SJu+blxOPV6YI1KVlXzs16/AX2EG1V3bHAiBr2DE53LrSIZ\noRENvLCIwmthAMC09RkU9P8XAOD0FRqT+8c0kMjZ33uxUXwsQYV7x5jBvU9zHEZ+h304dfgybo+S\n5pDdHIN6l5fUZRjDlpqKc2iFSrFw+jhqxR8BAJJyOy7eJV1X1y/i3hkq79Qk++s9/6fYnie99Fx1\nCX8zQLZOdwsToizdvrj2kpVl0KtzLIqmGK5qaVTmrubg6FOpm8dIk0fLo9AN0+ANt/1IiOsPuWkp\nPMIRurlI6q2zUke+zQUfOJGEr0FDEu4G0VngBti4TCdp1mjBHSeNTkV9EVNGGrMdixrGbTpNHQuN\nfmLZPrBcSnGkC+NlQZkvieLXPRWsalF0vF2Guky6y1ZOIm3m/0/IwwCATKuGSpULut+oQC1S1I1Z\ngeoeDVNCRE17OwXURTSr2htHp8RNT2owwyWOQHaH+PxKSodOg+PUTRbhVVNvUw4Z9lrc9AM6brjF\nzuBkDL5zMtw5yzXSyAv6r7iBURfnZ/P+JUS+xIjreGwBjiFRZlNU9dHIVZAd5zhYml3ED3Fj9lns\naIrN6ch5bl7VQzkoet9kv8Jz6MxxLrZ3otB0ea46IapfXWoCXxrlHL8cqqHopC6ebaagtrE83HsB\nju9cTjZQtv6kCs0tzr1qgrRrOitFd5eOy8jTwyiIKy5D1Q7G7YyJKEWoZxF3DTaLSCc624G9Sv1O\nq4u4X6aOvx+B7omqcEIkeIiUIzhj4vtuXB3Dgof05IaO8lSsCcz16Hz1qibcMHBDOls14qZIoKMx\nqqDS7Q+UCwA0pYt4t8qIYulIDMtNHisl2gQjp+oxaJ/9KABga0OCwFE6ra47esif5jvsmzyC6eme\nh3KBG/f2LSfmxzkvZdl9KEqUvyIRJf+ME5DLSSUvlf1Ixmijq0MOjInz5WaMeqoaDkCzKaLKJ3bQ\nDIkkHo0+zNmHJweZ08yjvsIz8MyZk+j/Eu1CHdyMI6uATcfNfVe9g/rN/xUAUPPeRuzT1Pfw9h8D\nANqxBTz67z4FAIjfkEJ1n3NbOL6HRJg61VyiHfyt9FHk17h3NBK/hO8scpN2P6/E/k8JKpReju/v\nps/gDxd5/NF7sA/DBJ2V9aYNc2POh8o2qB1QzQftoB20g3bQDtoH2D4UiNfdpldTripgkbJLVaMK\n+n3Slx2VAsMlejW+migAP5lHrUZqzKvUou2m56neSyCkpwdtkJAOi8hG0JPzd/r6JuSiQHxDMQJ5\nit7bTpkecaKnh0ZBROwr34dNJ9BxIoctL+kqW0IkuddqEQyIdI9txUDZJsdF8IrlBIJ5EZAiSaP9\nOX5fs9VEVUKvOFka4XslSbhqRDizuU1sOOhVTr4xjIKgl2q/QC/tsrEL/RY97ZrlB+i7SR+bt9bh\nX6cHebJJhPnyPSXsM78CAMiO/RXUF0jd+ud66Os51tY/oxe9e/Y3MT9LOucHzevAf/x52eLyRfST\nYQDAUQcjLG9HInCKpARzrTLSdqKPiHsf9a5IPj/Lu8Kmu2cQrxFRyI1m2Ic4992iDEkZx9hzjcgm\npk2iKFgPTUiLsI1zbM72kS9wTEoKPqu+PwG1g3cCKx4ZtJeoX2PDm9AZ6dHuVNlf9dX2zwsGwLoW\nQtFDBOnQcC6K2X1YxEX5hFKDeTXH944xDNMe0XZRzJVWV4VURnlU+ThiRqJcvSuKUp2/syqIOqMp\nIwJGjtnOFtBVEQ21Gw10Rxn8YwlRD3O1Cua9HJukV4XbHc7hVK4KSUbcfXYRqZSbg48/Ml/pIqfg\nOFgi/K4uN4R2hkFQTc1hSHbp5S/OqRBOfYPfbTOZ/PmMH+bHqcuat61ozlIX/e/NIPgkjzXKNlFw\nYauN5vjHAADb4Qgst7nOTi+Y0NkjAkxPcUzHXVu4mGFAm1s2AbVUUMZHiqivi4QdUQa3pEbmB8oW\n7FUgs3NMdHuciyXdOibdRDr5hh1oiGBBqRTmLVKO+Rafq54vw5AiTalsWLEVoJwS8zIMtjDl3OF6\n1fqb2OuK5DQSLdoKzvHIsgq77/IZyxLKGzFKMF6lHr1RVWIxy/Ep5fOwmagnOVMRrvLgOsMAsLXl\nx8dNRGGrtwKoWvhs2Mh6SBY+g0qbSPETJQNKEcrWcquQW+HayTT4Wd+5BV+Ua90v24axLe6cR+3w\nLhG9hqW0XVP9KvbNPELwxrfQdY2wP3E5Zo1ce8GjIrXurgL7IhJZkZ7DTId9DD+wIjeUf6hs0ckO\nWpfJNFqDUdz+Ouf+t09x3ioKH2ZGiZjPmW/DPEL28UnlYWT+jOPaPkKGLq6fg36DTIbrzjCiXe4T\nZr0XkmsiwPUu19V7n5hD7hXaEufTd6CKcz0c3Y5gyMu8AWsavvdTcy/hYw0yCjFVD6d2eNsj3q/B\nuf1+VanffqiM/2M7QLwH7aAdtIN20A7aB9g+FIg3KwogVGVtqDo8P5H2lNBYxJ20hhQFLb+zIhDF\nSNcMf19kQMrehUPPMz91XYVin4hAoeF5k62cQUdFRGzS6JCxi6CEqTiGr/PMQ6V9H9lq0JkU3qHV\nil6XnnC318fpLFFqrEUEGWroMKIlylBqBp9f/OwqPczZThCz4rvXo2HoirwzeVLzApCiNx9yXaDs\n8t/AzU2eL+5M/xCf8RD1XXNdg73GcdCG6fH/0nwI/6FK7/DUlTAu+hgwoZ/WY/8GzxXbX+V4PHfp\nPN7KE20t57u4fujTAACn/NuYWmUfVthdHPpZDVcEMxC2WgfKVnK0YOhz3LZFnWCXRAeVhv15uXYE\nrotEBFqzCwuilFv82ggAQHfcBZtIlVhp7kL+gKivtRiArs+5a1j4rGpoHnaZuHPdLUDX5fl9UybD\nyTRR0pqdMiR6Muhr7LNRncY5EfTiDB2BxiLOKx1EDiOOwWcz9r4Rei9RYSNBj3o+M4z9HmUwjbdR\nqVE/GxIrDFpx1pWnxyytaVAxk02R2XRQiKs9jVYDKlF/uqAUhRMa17AaZyCLsdVHQCJkV2oRe8D3\nycZFNrVOH+k9kRS/osFoj32T1XQwDPOcLp8UATiewfPWfK0O6RKvHCkdnONJ4+t4s8V7tYeLDWyV\nqOsSuQY6A2MMaqK+s302jeE7lDfTt2EmyzvTW6MFFLcop6/KoiX1BRkMYc7h4aE+ig2e+eV2Xkel\nQZTlK1HX660FNE8SOdT/1g7zNmv6RnY6UB3huaGsyXuY0puD77uqikZMaIhw3r9vuy4ZhyvB/8u2\nIqh8guOXlNfRzRORtWaJ/qYjZrzlYn+9qTo0IuBvKBaC2kRbUB3jvN54bx/jnyTbpF91wFCnDahV\na+jbiNQSDsqYulvFuLgS5szJ0dXzWRlTENk+r7Y5q03k3cmBcgFAUmmEKiSQ/9EcnAbOr8LMec9l\nLwPiyt765CS6Gf5/V+/HkIfPPTvGM+TYNQOaMtob/+N+THZp09KBMtQi1e68SJXablgxlqbtuvKC\nCZ/5C7KHd05n4RQ2ZrdDPcrfu4iFMfZrVdrHlpZ2alx+B9lo+qGyNTRv4Z/8BpmRV3vjeMzBd9/v\ncay39CVcDfFdT998DCdZPwORYBP656jv9ps8yy15trH+DvVzbqgEk4S62Mm+jCNgf175Amvtzsf/\nBO4jnGPbJSWWj5IJu9c8g0eGyGCYCuz3G9cCuHKRTNqnnzqNEMgujJc+gQsK6twXHirh320fio1X\n5iXNadmTQTJOwxUzmDHVFFRzugGzSDKRTHDx7/Q1cISoRMcOLyJlIC3SaiTQ7NBwxRLvJzMoQTfE\nDb0XCqLmoKJag340JrnwPAkulGp9G+5ZUjeyVRX2OgzwsmbS2K5xQSpVpJFkhj7Wu6Q8JsTd3r/f\n5nvcxG2dLu4vhNmHn5gh8Yh0ja0bkK7T2Hhj7ONtz49w4hEqf33lDFYVjAYsBg8ju8hAnyNLDN74\nl7eqmNEwOK08Po4RtbiXHL2Ak1/k4v5JgeMwP2LB3Zs0Oj17DZYdESUsm4Vaws29sUx60lKOQdH8\nCADgaOlNBAfI5kpE4OuKjatLOlc534L0sqjzO7WFopIUrGG5iQeX2J95CyPa+qEq7tu4scw1h7Ct\n4II1K4NQyfiMtTwXoNKtwniL414pSNATdZJVyiiiLjoTHjEXsmAIGpGS715BhZPiuCBquIjyLheW\n30dDU68NzkMdmqigluNYnFFxky8p34HWy7HMIg9JkXo0YumgZaLj0VBwwXdlEnQ11J2cLIW2ivp1\nLqvBVJHGxCro2F3LGDxxyi41lVFwiJzIG2aYhkRkdJTjYCxbseWkbNJ6C8UsjaDGmoFxj5vwlLhv\nHpEMrn9as2sgD9BQ9B6wWtWf1Jfw+QVS3DbZMrI6GtqieRPuDjel8jTvpE+NdSDNUd9b5ndxr0AD\nNRaehutjHFdZhHpWK/uwt0PD+ExBhlUlDZfFYsSdHY7rWS/XfO9OCP+xzs1ifvkEUlk+t/VTEz42\nxzWSnGf6yZjcNVC2Qn8bq8KZG26wDxJzGEkf141lSwX/OtfkdlIG7wka80aJwUO7WRdmhKPWcRsx\n3BfHOMMKRHa5iS5dZzBjXrWN6R8Lh/1oDokm14BOsQC3iJEKBelUzONdVCR0OgqOPXSCoprV8Cy6\nezTs5ZwCBtvDo5r9UjMior9zZRcuX+aYzBxjkE9DO46Kgg7cZH0XWyXqiWJsDVIZf/e9KxyTuU95\nIb3L9eRL97GVpn4ecxdgj/H/l/ScF7c/DHmdunTmBzlUAtSz0xEHSiP8TjPAvqgeTOFuk2PpSqih\nrtMpzioA5cTgYx0AeLr+B/hXbxGMfFV5Du9EuUHe1XCsv+gqwzDLY7QL7q+he5mBgG1nFTfiXNOl\nOI9HfuNze1iXUz813+vjyxqO7783PoXvPM2+j7zNY7Ti6WU4A3TqjP4Z1KTUyWothL/eprPyQoX9\nCj6YxMiLIvhv8/vALkFO7rksHs2OPVS2Qe2Aaj5oB+2gHbSDdtA+wPahQLwaK1FTuVtHpk3kJY90\nkYJI2TdcgzxBD3EoT2QRlvah8fGzRHIdpSq9tJ6sApkIjtI6mY3GnRxCdZNeT91uhq5CL7aeLkMr\nAoFaeSKHe4UxHH2H7mpUIkGzT2SQV5iRFdeI5Bp6QkONKPod9r2jHIQJgWic8gSfGIIzS4R5+uR7\neCsh6omOyOERVx0uJhgCf1z7NiIN0mwfDauwDaKoi6rzcGwRMdwTNVfndjsoxSnD9ed20b1LlsB0\nRosx1RkAQCkfBgCsNfR4Zpgo7u5YF85JyuP7mgGXj9DTe+EKU8Dd9E7A8oBXmoqHB1OWo09pULvO\n+aj1SPU31jowDdOrLHsckIqUeUMpF5KCes3WiVZ9fgmWRdBbpr2Doy16xJ1KGiov+9YQqOiY2Y1r\ncnrPGNPCKNLstcolQE3vNjbKsc5IGjDvEC3Jtm+jaCADYm1F0DHQMy2KK2PK3OC7rtq4EkYb0UGs\nI+qe9kyYtLFf7rQfDVHcQwk5zFo+LwOiet1+Gep19r03qkSjwb4P1a3I9kltWffFdaJeHgYbUaEJ\nAaTjRO5lhwTeHlHWlpro2ZuUY6RI2bdae3BZOJb9/Fk0Re3oclawJfbBOjmy5IcpS5SU3Ob1FO+i\nDmW+Fi5rDuPX+PcLz0iQ2CbL1Dk8AgBYzoaQbdLzV9+twPwRjruj8Com3yMSKR3mZ9F2Djov11NE\n8Rl0bKSis7EQjouLzK96qQOPBlTQikIZ5ks3UZoiypo/48BL65y3JzJc05lHCwNl01w7BtcwjzfC\nCo6pb08PTYRj0Z7yor1PebQeB5I5IsyGnMcGJo0crgLRYU2WRzkmbJPcAtkQkXAvxSC0RWUN6yDi\nm79RQnSc8y3diSJqZh9Mca5dm86I63L2uRurIC6uj+vWtFAd4rrQy05D/u7GQLkAwDWmQXxD1OOW\nyyEboh3z3RkBAKR8dxBr8/hIWpZjyk0EPhGTo+MiIh1zCbr35V3oXaRbUx0p7FKiVGuuj3vjIg9C\nn/pfSnYgE1Wa3NEqgj5uG/spOXRvifuwp/jcfDsGT5EyV7rAxgjt8ui2C5r24ExqABA/68Yvp/8d\nAOAnd+agL7Asy+8F+Pu7vpN4I/EOx/SiE8OnOGZnpE3URFGWv3WLlLwXH0P7M1xvL+WeQ+xFUsLy\nc0WcvkDUnJ5jf1u3N5C6RT00fN6Ju2EyKgiUsBzkEcCKg+P85S+H8HaTNrrYvQ/nKG2erP9dNIc/\n8VDZBrUPxca7d0EY0UNVmNPUSIOqhJqeRk5VUKJpIo1gEZGiJm8dlSo3GeW0Ga0ujVgtbkGvxY1s\nqEHaxW+o4VU//z/XDaMh0nu17m4gXadCqjW88+od92Cvwmd1szE4nDQKajSQlZP+UBbF2Ye2Blmd\nitEXG8jfb28McWF+JKyD4S43gJunnkd9gobU0C9BO0eDKf08J33t5hhG73JS/+BkBl8wsizgJ1Z+\nBIWgtt74J3yvMZVGIkCL6QvNYJd2H/4rt7A6wgjTY6JAvNrbRa/NDemp96ywPcKFcMFxHR+1UBFX\nRWo5XTOG+5+k8VQnBqd62/h+BWY5v9Mp8h2Tj7VQ2qLBlLQTGBJ3c2/5lzAZoGHaEDRxfb+LGQ8p\nQ4VUj5pc5HBu2hGOMjLyMR/vIj5wGGD5MQma3vFRXNqncVyc9mKENgPmNc5BdEGNSSsXZk7ihsIv\nSile/8doungeqd1lH0KToYGyZfvDcLVouAuCwl4wulHe5ny2tB2oRPk9SbGM+qQ4QxRRxgWPAYo2\nO1aqTAJyGjOLtQ1/jQ6GQUPHsdDqoFTnON5PBDGkpZ6ozRKs3afzOSbOBLueOPJpcc6vVULXpczx\nsXU4RIT4zhD74OkNLlWWqSWRVfO5PQadw9FKwaQQG3e9hsufY99wTofxybKYPgAAIABJREFUTwsD\nHOY6Pe99DJ6bPB+MWJJQbFIXo8OHkHyLa88hUk7aSmO40eb/nxm+g/UoHbGTS2qEfsQ5Oi7jelqB\nE4+JFKsZtQkTfTqXKdk+5sp0rjZclHcxPthhci5cgFxU4Blpc/PLukbxeJQbaLD5FlIyGklnPY2y\nqHA2LRK2pFM3UFNS32X6BhxGyr5+51swe3mPNOqmzSjpAtDe4CZzx2ZDRaSJNPb2ITKdonyKRv3G\nTUChp872TVPQ7NHeSFUqaNa5Xna9Eoz4xZyt/Lxs5aYSRzp02v5bZhezfToLlxZ5NtrfqkHu5uZk\ntvSx0yZtH5GfAbbZD4WSfe+0ZhF/hOMjLTlgf0C78ratjtkHtBuN91Py5ppQTPH/d7sR3Aoxoc8n\n+iFsz3D9dhK0H5ZuCcEYddXvPAxPhDYmObkNhB5+11X/5ttQ+v4Rf5faxMo8j+Jkgr53NW5i8f24\njcfLKEQpz3fNz6JmIjjq3uN7/42jhZnf4hqoTiQRuUwHefRIDd6f8P5uL8hkG/WlMyiNcg5fL72J\nky3hoL3yPDxqkbynQv19zxPF/n+izmqeTeIPwrQL//nyE0j+74cfKtugdkA1H7SDdtAO2kE7aB9g\n+1Ag3qaaVNRoVQWDUySILwDtLr1CeX8OWhEncrkpIgObeZhE+r9UTI+SQEv6hhq9AGkpW4/f3XZq\nMSuykxR6bjRT9Ox1DSX6ZXrxahc93mQoi9YUfzdiNaD2gCgiospAWaO32RglWnK11Cg6SKvutwbf\n450NEwFM/2YXayURLWks40j+i5S9MYSyyKTjeY/9Nnu/iV5EZPV5s4OLp0Xh0fYZKKeIxl19ouMH\ntgSsIlipnp6GMU66ZX5sDG8GefjvlRG53doJ4xGB/rbQw+4Fyjn5lSSGZkSVoW8TCY2P7aIfpYdf\nbAymLLvWo1AlmcpvYoror57RIinqwi5nDqO4SA98en8XOSu9Y5+EaGUhU4eqRoQDnxKatKC4pm1w\nh9ifUob9NWe1CBymV76W6eDZFP++ph4B/Cwbvmvj82dlHeR89MDVaiusQSLPHYce0zWO8YZMeMSS\nwV54UtKBrCJQvKjyVPYaIenSO25bQnB4iQqDOw60d0lf2lyiiEdMgjyIvJI6KbQF6rjcNIKSqPKT\nUrAvRlUMiiop5WmJC40q58t2uwKLiWgwr+f4WtItKOyUc1pbxY4oON/suCBzMPpYn6KuR7O9gbLd\nr1owPCaC03K872jeyUD1NJFePdzGyH1Snh1LA1VRlX2sw6jnjDaDqINz8VWpD5dFsYdhxFE+TP1M\nPUJkVf7Rt/CUk0ce52bUUOIt9nFlCIGT/G6izbnyBBfQ8TDAMFaPY6hKBLkZfhy9M0Q+qnWuIbmi\nO1C2jFkDf5Vyx2zso7lVwZqO6CSU98MpChfcLyswKwLcQqOUV1+fwZ6K4zeuVCMkasBujw/DL5gI\nc4XUJa7bYIgRxa4FUlCYuHbSlS4MMiJ7xVUi9HxHA+UPwwAAjTKHkoS6U68q0DpG/bJLKsg3Hx6A\nNJzp4xtTRFxDK8dRFYXlMy+zv7KjozgeoT68WZrHoWU+98adJvw+jokxSTu5bl/FoR/T5i33q0gX\naDd0I3bcMFE3Sm0GdX5WNo3b73GO9kYmEa3y/7f6l7Cbo51ySom+e97DWK38EADwIPVDTCi41rUK\nGxpD2ofKFlYXsCbSAbs1fXT9HON/3SGS/LX29xDTkY0zvVPEUz6ugXdn/wYnCoIt+uLvAAAMqQzc\nv/3POGav/hF2z5MR+IGjgaeblPNVcbf397N6fEekDbWf28Xrw/z/idsR2KUcv4yauudt1XHk869S\ntuaL+H+OU6eeuqvC6xOrQpLPPFTG/7F9KDZe6SQnxJB0Qh7gglIlt6Bpk9rdG6rDGxMFyPOkLqsl\nwKGmUS4kq1AtUglzzTJ6aZEOT8WBq+y2YJ3mgLpSXaQaNIJNeQA2ubgCIKjiOpIYCXLBykx6yGe5\n0M1rVZg6NBSypqCVDTGkq6RPVbXBSjVr58K+lpiCJ8ANf9rqQvoi5chOyVEaoqHVbXBRXf+2ATPP\nsl+yhhyPX2cf/mLibVjO8EzFtU8HZUlqxPltbnQj0SKGHxPJFSRRLA3TEGx9ioqzFJEj/AManYVf\njyH1Z6Ks2O2TuHydFHR96ScAgL/c/zR+cYyLeCG0hlcGyOZQ5iE9TWMfa4sSbsU45l30kjL6FKLi\nelhFasBz4Nxe7VD5Sx4vqtpnAQCjpXOwu7mwWpbrKCifAAAM2zlO9XoH10ZIGZlXGlANc5MY95VR\n1YsNe4M6spqQ4LSR72oX0+jWacwy5gW0Qap5W8E+jjUG52pe1G1Dt0MDJB3mfI9JSpCa+I7NxAzK\nBr5D0oii0OHiV+1z3nIuBw6paLQL8jbaXW5EhvVx6O1hAIBCjIOkP4e2SGlaNLag01Eec0OFkJyO\nS8XNCixzcQkUw+xDMNTHUQ2dq1Cnil09r0jlRHWoyXZjoGz6TgETeyS73hE3AE6FvopXHmG60eNB\nBQx2RjIf9V/Gt+siz++MyLX7Izn0J/nsyJFVyFqM1r2Q6WFKLvLedqk7/ZkJXGyIc8VIEwGR1rIg\n0yBynv2cWSaVd7Gig3VMODBKLaRmMe6NJPpb3CQyMjoK7ymeGSibv+mDtMXvOEVx8kggjymLcMY7\nO6hVaB+sG2F0/OznhJM6Ek7XoEuKakEKDRRT1IExWw/dO4x+zb4fF2LMYvIw15st5ETbSCdccikP\nyTCrXnX8/wAAIH+wAoNIL91p7iGvo1PWrabQNVF+7cYspIP9dwBA6MxRJO5RjyyT72H4Gu2bbkpU\n6okD9wMcX382Am2IzmVK0YTiHufgnpuy2asBFIfoUX1jfwEtqSi5hzpsVW5KhjDH5N2mHLsfpb7c\niagwJZxMBErQ1wmOkiuktcNTeVhG+N2xtBtZtShjWjPA4Rx8gwAAzvz17yExwZSP/XEldpRfAgD4\nXv1zAMDXR+VQL3Pe3EcDeO0vqDsm6Si2phlXMBdlatIL18aRvEK6PDt8CqkF2r/fvhOAusZ9YvjX\nuPa+GTLiyVUePUbG/2d81fx9jtOTPVx/nf8PzP8mAEAV+H3c+hkvDD3zyDWsObjx7jx+BLpzIlnN\nxx8q4t9pB1TzQTtoB+2gHbSD9gG2DwXibZnpQe4mNDCKgBC9cQiSIXpIlrIb3T4pEinoBeu8Mmy3\nxcX7gAozRXquSvk44qJKy76SHp+mMo5ElP83dvuAkvSyT1HAZp7ftRTpdS7Z1Wh2+PeipQvjGlFN\ny2tHyy6SZbRETda9FjpSBn30tT8dKNuUndGfZ2R7ePNJPiv4IAfZWSJP104T2htMQxb6Ij22sfij\n2GqKRAQtGV5bZiDAsiyBSSPR0FaJFK/DYMX8j4iYE2NtFE+INHLZI1BV6Jlm/paRfMfdPXx6nqjo\nG+FlSJREZJGSAWpRK9MiCnQ/NltA7CLR/Pn+4OQgea0M6jDHfVhByklTLkLnEZVt+gmMiDq0E5MW\nxEUgkLVOJLKh2MSRFOkl5dQSZCIwTNr1YUxFr7vYETVF431MShll2NTH0W6R0m2qtiCL0X+cbPK5\nrnYIe22OmbkYRt8okFVZgr0e0dlTFXrBK+rBNHqooYHfTV0ccRNZRIxNWNf5LrciD2jYt97sBKb2\nRUEEJ8dD0g+jlOb4zfbqSGmJSjC/hp6ov5oti7vl2rvoWNivQL4BnZ3fjRZLsIqC9Y4Y35V2qGAx\nUY+09T7Ck0ROpuIOTOLee1Uk2Kg+pIJPc1qGN9b43Vk3EV378zdgDlAf9MU6XrfxuZXkHMaP8R6j\n5RbRtUOiQSjJ3+1K9di7w/cYZnehEoXC5zdZy3S7v4JYnIjEp0siV2ZU8uaqHZJRorfrKj7f6b+P\ndoV30tuyIt4QAXtDHiv2NKSCDTv8bLqVGSjblrQEV49rsqTkd10PytgQiU+8E3lIdZzP7IwPKQOV\n7n6aUWbSfgYaUZ2oFI1h4Rplbvkk2NdRJ/vJEdEXKzY8pFg3FA3MrIsa2mdaSDaof7JrRN/7RgWO\nqMW6sAIKKfV+WO+AoU5dvHroFkZjg4s/AEA3eAHPgrL5Ei58rUbEpVPy97XaBFpZ2tKb0jakb3Be\nsk/1sOAkddsKv8g+9Iqo18kC3L1Xw/NLPPK5FR9Fry/uGLu5xlbvl2C9TIZj8ZUmIi4iz5sSYH6C\nn+/nqU+QOlG7TB24fbYEv0kg4fYYmvnRh8p28Y+uof4dsiyns3I8kWEQVF4kJjJO+2FM8f+S+zcx\n1yf79c2vPI+JP2EQVNZFnZ04XcVSmmP9hzcl8H2Jtvbq5E+RHyObeewc+/Ls0jiuOb4OAHg0Ykdf\nJCNqWyXYP/5PAQCBx9mXq1//IvwfJzPVHZeiEifjWk1XkTE9VLSB7QDxHrSDdtAO2kE7aB9g+1Ag\nXrW4ooGAAQWFSLnn0UF5gZ5TcUwBhbhCIZ+l11OvaTCloUe711tBVEUPvCntQpvj5+ki0axGWoLu\n/WCaihX1JgNq9ist+Ps82+yJUmztQgF9K1HfdtgG7whRrnp1D7IZeuhFN8PwDSUXsnp6ku29wVc3\nttP0GuPxRSzk6V1XhiywvcWzkcxH7Jh4g1czNHsM08/oJaiPilR2X/g0fuc+Pdd/5bwMeZ4e8dI0\nPbeh/6rAT75MD/Wrshaq/4Vn2ecn/XgxQ+/svE1kxlFU8ed6ojBlZQHHjxCdhexe6A1/xeftfhYA\nsBOwoSDjmZYTg7MESdUrcAXZtx0vZXtmfBgrbSIKl04HY5rzWe3FoLfQG2+b6DGflXhQ9/B3eose\naXF+byyW0FHQe23UeQbr8NsRl9N7lpgKQInvUKQOAwqiIXec85Kc9EGj4Nz3tk3YPUakktrxYLQi\n7hvXRGmz3hKAN35ONn02ArWWZz/yFJ9la5og8dFXzcutaIvgJX+zhaiRZ2s2hbh33HUhP0Y5d8tW\nDCd4Nv/A34VOBKcMK6hbPf0IMgp62k5HDnsbfJbpUBH9PINLCkK/u80MHJuixvEjHuSVRJD/P3tv\nGiR3dtwH/uq+77uqj+q70d1ooHHfg7lnyCGHt0hqLeqIlaxjpVXI2giHLa+9tuV17G6EbFO2wlpp\nRZkiKWnIoYacA8O5cAyAARpAA32g767u6rrv+67aD79HrW0UvN5wxOx8qPwCRHXV//8yX2a+zHx5\ntLMK1HK8T5O4RKedZvQRvADAd7MKSR89xmlREvVhR4UJ4YF39qp4XkU+25ZrMLNPWiutXPeP63ac\neZL7Wlx9HlUzefVoXo+dFtdj6/gBABvlXXwtxndtm/uwMSCSGSUlWIb5vLyUdJJ3bIiu0zvxqPzo\n+MR93OZttCcon2m9iHgZF7viZq4r0T9K+ZZG+d7giB5D4s6vZtRClibP1Ye9SIsuVrowI1Yz/mHs\n7pL+/kIHWzXOqbaOOCHdo2xFzcRBV1tCUUQvinYp0m5GnmJXakjpSFf7MNd7cM2CpIG0Kce8kImh\nBHfkERi8HEAwK8tgLdx9vCgAqAcVqFxhctpSXoepYd57f7hDuTAmt5FOcG2DY9OIGhjdct6QY0/k\nDRiFh16eLyPlo06sjDTwZxrS4UTID5ucdA/ukwcaJiucC7wTXXreA902aWko98H4A8pD6zR1pjN0\nGbsdRr/U4Ye4qCduS+ZxHDvQXUcCQHNwEfvnKaeX35Uiqj0PADjzEvFJbG1hTQw4cch9GD1Nnuz/\nYhDOC4xKXO4Qx++qb+I5JfWjEfcQ26JnH7j3WzhQoHd77XPUbbp8C3Wh7xffeB6t438GAHimaUJx\nk/XaX5NzT147Fkb9Ntd1b3cd8Tb5zHL6BM6Xv/dY3LrBJ+LglepEm8NUC6OiN6+yM4LmGQp0NVDB\n0BgJ/TAslIuhgsU6ww3Wgh9yDw842ZUq9NSXaJeptAoHGnBHyeiJpA7yEYbqzEUllopkOMcxCoq2\n6IQyxySoY/UcMlUx27TaQKssGFFkxuatTRRyFOJBhborbsEyhXU4/gDbT/MQmQoOQ/RDwO6HWbwv\n2pQdFlmR6pdTGHvtvwcAPLh3BUtzfMfPGnSIiXDLbpCHYd1/AGOnRKjuvQquPEVh+rmHCfz4DJl+\n2sgDYrX2AWR3SZxz8u8gcp7hltxWBoMVkewxx4SCax/YcUIYE2uy7kOenRED2k7unUnOxJx17TS0\nYYbRHMU6igdpBHUkh1B1cb8O32MYvXRWB8cqkxJU8RqKZsZrNLUiUmLmp/8glVmibUF9kyG1vlYR\nBRcFPpXdR9BJ/PInSF9dsgqrnHySmM5AkWNNcP/DKPRONiC5rRI1r6XuE1MKMhl0LtK60OLeyh01\n6MQEJHelCYlTCJ4mA8uOMMqGyGfv70pwssZQ1ESngMQgeW4sUUVNKfqDm/fEGmxwFKg8k3pAIWHC\n2mhA8beHdzMoGssogZwwhKLRGk40yLdv2XdRKpLXlEkak02VpztuEhsUa7wCWTwuYmSqMLQx8tH8\noTnMtKigJcoa9kTbPuUdPve0J4sH7wmjo7IJ1yT5ZN+UgfQ9PjcsBqB7pSO4WqYclyYyiOuIz9Oa\nY2htM0RYU/EqxL23iEyHvG6aksF5m2HaPdsh1OZpXBbslMebkS6FrgCqBxyoPGDY1HmUvDkVtSB+\nmLJQ2tMjVaaMdJbX4RDGe+0IeWTv4SaWZsgTw/2DMPaJhitraZi3yNf5L9I4aFYc6LSolN1LOqyI\n1pfOAxqM7fPQT4trkJhtA/oK5a1SUMBt8QMA4oYMnBK+T36rgf5x8tqtG4/iZk3PIqQgT263Sujk\nyQejMhowBpUM95qi4qIRwVqT1xc1aQz6Jg/9kyny3NrkQXhBnlIGynDu8ll7U5sIbJFuQ0OkUywU\nxCt1KqxG8DW09NRT5VAGUTNpoi3yX296DgUf/28d/BTuJGn8fapYQLLUvb82AJx80IHMwRa1HvUe\nzAt/AwC40WZtr3e8Ae+qCFsfjSJVptER+U0vdmJcr05Mmhu7lsTlL5KPvvS+Gs1vku758+/B81ny\nu/yOSAA7o0flEr8r+8U/QzjDpiLvVDZR1PF9T7xyAQDw/Mkyft7Kc+YfGKt4SSOuRQfUWKzzCuCz\nj8XwP4VeqLkHPehBD3rQg48RPhEeb6RJC2nIFkc+ylpBvXUTsjQtlbAzA5PwhmTiUl3f1CFfZRgC\nqiIkEVpsypdLKCdpndnERJJ6WIWMkl5ESaVEPk9LLl9UQTZI2yMfpmdl0XTQstDCf1iKohajdasx\nyJEq0to+UGFCgazaxH2RMFF+2N2GCRq4xjH9HFo3/woA8B98GvymlckIt7bb+NLXOT3j4fq3AQDO\nxCw8PjGpSG1HfJeJVM7yBFq36Wkc/l3R7eav5Ti0RTxfPzoAwyat2CuZZRwbEt1xvkOr/a5qCjMH\nAwCAd1fPIf0uaWZTRHH7CMM0GQ+97/HdAOoztJg1iWJX3Cq5EtoDDMN6c/RaGiErWgP0lsKqIWgq\n9AjqjZuYztM7C4ii7COLamwMk27rYS2O6OhB2nbs0BlF0kZQlNyoKhhq0ePK21tIykSzd+kwDHpa\n856M6KBkSCKWpGcw4JBjoUovzDGaQTDFErXNEZYVvZy4iNe74BZQNqGviVKmDuknKxfhk3Fde5UW\nDA6GuKOtITgUjAqEwqS/zytHNMAkKbneiZSe3u+J5j6Ws/SOi3oxgEPZgFnQJp/aQ3GWIeiNgg6a\nHL9jPiK6tK2OY0nJ/XDlDyBp5HuVGw6UpCJ0OyOGUPxN9/aD+ckUSlcZVv7sKsNpr1y0QiEmJF0w\n6fCwzPVMfFRA28wEtDZZBOtlN5R10rRy1gjTNv+e+LCOhJ3XQ8NqJhfVl78D6UmGHssfrWHQzJaQ\nOc33UR8grynmKWNBmQoDB/mSresadGTkqZz3L7Hk4jM+9YC89WPLQFfcLMEakqJuOBdi/fbJuhoF\nJT2VgqIM/STp5FrwIir2QJLltUx+2oPzdfLR3t06IlP0YjVmJxSz5MXDDyjzgcEmWgFx5eFch1Hn\n5xqqawhyuyFbpZfXssmwv0vdVdcAyQL3cESaQ6NG3NLfqKI2X+6KFwDIbQH4T4tkwzQQmGfIV56g\nvir3xfCECH/uLT5EzEhPzj9og6JDj/4Pk8ThojmLq6K6x1LIwGhgFErdOIK8aFma2ha9EdQx7NQp\nx5bGKFwuyoW2rIJShHSDq6KOtV2CUyZKKyWAp8iEyKWBDsb7Hj8AoqVVYTREbz38og5fukfv9Vti\nSIgifQhbgwwPq4tH0FLxii/9dgD6o9SxfUl6poMGFdTfFTXVU29B8gu8Lhi+9gt46yP+v64RHaps\nbgSOcr9d2WGkm9QLvz1jx/wCrx9O/iOeF3+hPIm336fe+R9zv4ifiIlZo5nLyEZPPRa3bvCJOHgd\nYjB4O55EoZ8hqlTIjEmb6IVbTSEtJk8U8ryjUzbL6Ihs21JDBljIUNV5K2wDPCBrYwzbjG3HEKrx\nu/E+KWYKIhvaVUdEhBENSjGGr16Cocp3ZdVhSI08sNXFPbiLFPZsRjRAOGCGqUwlKvOUuuI2Ig7Q\ntc3DmBF3CV9rfweVLAfS/4zUCNOltwEAL8wwfHKzFcU9cV/x6R88QHiWYbLW8VOYfcDNrq9SObdm\njDjT5MBmVfltxFz8/8GzpzC9Sib7wf9EYXSkDTj6bykg0cFdNKapHdRlLUZbZN6JLEOB/06qxmey\nFPLn7AEsdcFN6VWi7CdONTGObEdbRx+oSBzOJKqjFKbje2dRDDJMO3mIh1MkKkXfphhCPZ1HosFw\nbEHmRVkuavZUzFQ22HJIecmuzZgc/SVhVKVyUIdIq4To31rO9sEYp1IKtCUYV/JwiVlq6IvxYDgn\npriEtIEumAHjS0o0xeDtcj8NGP8HPgSeIJ/Y4k1k5aL+0pVEwUkFNCyuKQwZHeo6MQlqVYfKDA+B\nW9pRDA8Qz3SUa1FFCsABGn7JohFa0ThCposhk+UaLFEqkp1UEH1nGKpurm9D0Ra9sDMBSLRUlKEU\nebLjaXbFLZ50Ys7NUO2OnTx3cT2EQIaHRPHNJFpnKJPZySBSbX5ujVBWTEP3AXHfKV+sICLlGrX9\nZqhMpKdeNMWJPjOF4Hs89KQvO2F9n7hVypPYKVH5GUXy9YNcFmdjpFni0B0MVUXzidyzOBUTPPMk\n79iMD9a74hZtmaDvkFuVeu5xIG/HQoxr6KwFoVCKg0XbgLlGul+vchEuhQzrNcqyQ6+FtULc5fYE\nMjbqHr2oOMgV9dCKPujOZhW1VeLc8NmRyfBUk/hFT4A3deicZvy40vLB4+MeKusj8Iu7z1t35Dis\nKXTFCwBaQ26Mb/JQK1YViIfIP2fP8IC4VrXhzqvEc3xqAK5t3pmi2cK+mLCjrpP3yjUvzGHSqRUY\nRUc0jtClPkSpchEAULdTVyRNx9FJiH7dZ4vILPG9arMFkYaoYx6hcVrfLMNSo04obUuhtvK9Mt2X\nEW8GH4vb3bEXcL5Mfmi23Yh+mlnmiR2+d+YvbsF0nHkS7dImtkShRecbVsz+K+7LWoyG5pHjUhSP\n8LCUTgxg53XywbivhtkQ+f1pJx2837uehL1xBQDQt/IZHFPwzIm9k8D1X6VDNPEaDY0Z/buYa3Kv\n7k7X4P8RcTaoqkgbul/HPQ56oeYe9KAHPehBDz5G+ER4vOYFWpCRKT/2xNBstakNZYaeq6Smwb5C\n1MilaK36Ow1otSK7U21FvU1LMeoeRm2T7RS3J3jhnTEboKnRwvQU0ui0maSzLVHAV6PVkm7RWnLK\nOshW6dFq61IM5uk97Mjt0Mj5eUx0qEkUm3De43Pjnu6ktO4RN7nzEObnaJkp5E/BLiYdPbmzjh2p\nHwBwf5VZzS9+7kO8/Rozjj/6sg3narQqr39nHsbTtHhP+8T0nrdDuKSiReZ2TiE/Qust7rIgJTp/\n2W/8MwBASvpP8cdj9A7Pur8Ol+e3AQBHNw7je/eJp6JDT+eU+UdY1NCbit2vd8UtJ3fBvCjaaMro\nDR2tFxD10RtRPKhA2RTDAToxdESbt4aSOPgP5BAJMPxUW/HA66SH3hzfhz4ppj65RUZ2poRkXiRR\nWGLIBYQnMdYHSZpREmWAEYk5XRALIgnqVF6CV3do5eutI0g/xchIdpX7YojMdMVtV9XAeQ297rVl\nrlt6NA8ohDcpsyISpUcxU/AgI4YyaKqsQ603NlHUi4Sofi3UPvKyOytBY430LIKh86rhLpQVRh/K\nFR9UeT6rsGdBs4/vSxnpOcgP2FDcoJcWd1TR2ieeDbMe+iBDizHhJXcU3et4C4tVvG3m7573cK/u\nBeegnSRtbh8uoO+7lMPySzt4OM+p46NehveKvj6oNkgbW/QcZC/Siz15t44/l4okMZHFbTAH8dkM\nn7twy4u06BB111HBsFokpNnomV9YMuC6hvwysZOCT0IvTKrJ4vo4IwnOG/TqT6Yt6FY5P5kvYMPF\ntn1mEUa/JX8PvmExOajQhEkkt92xj8Gi4R4ORERLWZsCnhwTDSPSEiJKelz9yjaGNsirDV0AAGBv\nyKAVE4ey9hT8M6yFv51LY1TK8G8iT32l7q/CXifNg1Wg0iBPmTw7+PAWZcci0eCax9cFK4LdbUVI\nJGh5IxEcFq1XV98T+9N5gMhZ8tYbhQYOTROP7U0Vjql4NXCsSd7aU8chFZ3/rOkBVFWk7/2NObjE\nVCPJOvlTOlbGZJi/i96bxpk+XrfcaRQwu0WeS7XoCU4+24d8mdGZY6Yi0h12GJs8XoK5qH8sbupW\nAukTlHX9O210fuIHAMx9hdHAzj+ZQvo25Unhr6G2yEQsW7WAvpcY3Qpdohe7cr4Dd4F8NnY/ic94\nSJPFzntIFai7/2Sfazzi9cF7mkm4P77+VfzdKpO6/uC55/H8e98kztPkyTnvfdxfZ0RxaLGBxFnS\nR1vI4uJA4rG4dYNPxME7b+ei+91qOECCZaN6hLXcTK/chbYoFbGZPz/CAAAgAElEQVSZuNE1YweR\nEIlXUUlhilHgG/4KjFYKwFiThCnngyjXeEDsOPJwipaQrWIVSa8Y4C4mpBQ7NagLVATOPR+yh3kg\nR/Q+KOL8riHKA7SZbiCgZigZue7t+dR+hlrN+S0UcmT+o1tB3M9wjf/bUTl+x8VtsIgi9FvfKuGE\nnHcGHxmHsR6j4rowYcdDA+97/yJHAfy8141WSzRUUN7E0BBDTc1LTtyx8fOB2N8HAJycMWBcXL+Y\nCr8NvPkEAOCN/jD0UjL1ppMKtbhzDGUdaa14rgS88Shu8UQT6il+p7ogSmCm+6ENE59GPYXZIIMq\nN3w5HGiLFpUrVFZBkxctteiprAKGQIWYXzNgu8wwrjXK0E/UK8G0KD0KZbWQOrleTek20i7+Tp3h\nGuK5GzC0eHAvSTswHBKZp7F1/OgmlbFFTKPpG91/FDEAsaYadzd5wBkPE59S2AxJgdmqlZYKfg1D\noTGLDAYZD5pii3y6JmlhVPR41vp1qFwjXQtTVeR04lBTxQXuR1BK83pjIglkzTS0pA09Ek2+r7FO\nHPTVEDoa8q/tQQpp0ZKvUZMiLxofOJL8zWqx++g80+EKlKINZFFcFZQH19BpMvt4ZFeN3QPcK21z\nDKdFJvJmk5+110uQj/EQkgdy2E9yqPh+/zOwSrgv7QCPxaWdJl738/Aaj4xAL6aAXdxX4G9mKN/W\nhzyQLO44GmWGY/MfjSDs5nddmmlMG0Tr1bsiP2Owe2lKxqjFuJkZ9hkx9Uu71I/ONr+f28siDOoK\nheU96MQdZK1EWSntO6Ha5e/6j0XgGGBoO/VBEVUvQ6+ioyJMmgw2JFTajnISISZhQ6PyoCPKtQpi\nYlR7toL9OnlkuhbDfJjvSNQl8PmpO3QdA7xShlu7BWXtu07EK9RN+1o96gf5rbF7wpicPoaJAvdC\nE9LgiJ847b7Qh9Y+rzruSsV1gWkYDTFCdC+hgttFXrfLfHDrqTcLkzT2JhoW7Mq595MxBYqzxMkb\nOQLdCV59qcw8VLc1NVgyosRoYBCTE9S7uwUtZia6jxcFAEfbBdsP+d57x7chN5CPrr5BPnvqwDga\nSvLGpx48jYi42vv+D97AG18jf9ZOUC6yf/kMdL8syoZ0x3DnA+bWFL3fgOIE9crxPNc1lJ1HJEmd\n+Rv+f4/VBmXyF7IVwMYMZ91z/H3E82v4jJyyuXmgiDNXeFaFDz5EMPF7j8WtG/RCzT3oQQ960IMe\nfIzwifB42wO0atofxRCdpSWObBUTbnoBa+E4NGJebMpIi0W9HkVpgF6AtBDHTkkMD6incF3kJ7T7\nacU5C3LYRHhkoJzBtrAah7TAsqinPbXC58ZMFrQktIY2D0qgrokEmUocxQLDVYWGqLubcSD/gP/P\n77u74hYWDS/ieidUW7T4ftAeRr+JlqIx1cZfK+kJ/4qUFv629kmsiay7wcwWTG5amD7zB5C+y+zE\n6N+lJ1iLF6HfZrjwP/imYbtBWp4fXMJMXkwkkYqkpRtpXBWTWWYHXWgeoxXcue6A4TBp5Rn+XwEA\nu9/9dex+QYQqr+x0xW10T4usjr87fYiJJfm1OShG6OWXbEVc1pM+B7MjcFb47ocn+V75wgEo4AcA\nJCwbWFnhHvt9Q6ja+E6VsL77QhVkkh8BABTFSZRFm8FGw4uGRDSRaDFM594Zw/wErWB1IoOYXKRv\nehU4F2OmNqS0Vq+r+7riNi5JojLBUF5V1DNnTFUYtWSYzK4OWi+f4Y5XEC3TG5Ko6WnLq1KURHJQ\nCTK08sRdny1A4xPNQWJi3nTmDqpiznS0oYI0IrxQdRCdCkOgiofkyRW3B2KwDYz1OhJVMVi+UkWh\nKa4cOnyWV5dGoAtuhnkrXKIdq/J92t5T1TYuz7Jln2VwAQEtIz2u9TRSFvLcXIUhu9haCLcmuS8T\najPqSbY8/cvMLdh3xIxh4dzUdRoo9+gNtVX34EmRJu/lt+B9nd9NSUSIXG+G3cI6a4W9HztiVvNV\n1z2cFjOyTfscqoHGZhfMAMuACqkUZSBkEvW6TxlhvkN8/QcdeC1Br+U5lQKyGK9mdv2MQCXCZajG\nqCsisjHIVvh3p2IUmZqIqPjo/bW016CukH7yXQeaJtJM7hnHivjcXhQebz2FTIw6Jjnmh11Nj/e4\n4QhCEV4rpXIGxA8/PvO3aG7ihBjq8a45jrEZ6rwNCZMvLUsZGJ8RCUiuEUTbpNF4qoG8iFaUReh7\nyuHAglWEuL/SgKLFv2MZSCm5R1UJdZpz4AiuHWdkSH25BX+LCafL9TZmZExA2ixy3X3KOEZ85BOL\n5AgMonnKBdMcdDe7J8QBwPjCTzBo5TVNfL2J7JNcw8/nyPf/1+FrKA8Sd8kPjHg+Qpn8+i+chFFJ\nGf5Qze/Gzv41aqsXAQCnFA+QC/P/kltLWPs58rjMz2z1NzanMFvlHldML6Czw2vKzaobGgf1lOsO\n5dXmrUElrmYqHwzitdOMnnk+moJk6Kfpp/7H4vgfQ8/j7UEPetCDHvTgY4RPhMcrExf3qalB6Iv0\nHBo+BV4v0gqb00RQEfNZqz5arlq9C+UMLTaVXY6GmhZQS1aARHTs0YmSBkerhuV14TV2CpCLtonB\nwjJsST432EfPNFcyoF2n5yXZ2IJcygSlilWOgoJ3Iqkyf+PeiKHPSiu26Y3h1uVHcWtHeN+UNU3i\nORvvCp40PoeAmBGrG1Mg7WOSQ+UWveCBmatYsvIOMp4agKtFT6ZoP4i+F0Wpw+tMCpJjC9vHaIkP\nzXtwNEtL7krBjXSO1u2ZaZEksbuJkwp6qFLpKZSVTErYM+WQe4vt5RZz/wsA4FM/a4Z/hFbcdunu\no4gBwOE4aqJVYqBIT3LwUAOZPL2THV0OM1rSOpqNI5KiZX9gnvdigShgctLLl1T6Ue2nN1mWWRDL\n0qP37vP+ZX2wg2iUntegM4SyuPPsGDb/dj/v7fH5HsUHOJWnJf7GXhkWDfmkvqXEnSBpaRNlTv75\n7ne8W8UaDA/JB14TIy/tfD+UNeFJD8qRzTHZqJadRamf61TLxX17KY58h3tU3LoLh5hRvJWtwZfl\nXepDOfdSGjOhT8l11aT3sdXi3hsSWTSk5FvniChXk6ShzxD3QtuC8h4t8I5RD3+YHmRYLdo5ZpVd\ncfvImMHnFAwLXdmldzLrsWFonTTZLhrhepteqHRSj6kq13Njm/hahsbgkPEdDxvTKOyLe77QHOrn\necftuMN1V7NJ+G2Um1jDjOI2owRPedxYrVM+r4na03K7jnNVlpE8eGIeqau8f5WNuZB9SLpvfYOR\njhM3Il1xiwcV8ErpTWYyjChYvcAtUVt6ptzGgT7yy6bqFrR1RkmqWtLK587CLkqLZGobLCLXYHE4\nhOY6+dNygbqmUxuCdFvMbJ0NYFpKz75qkcLKqYCojIlETWs/+vV8llQeRktNWr8b2oP5GP+fTuxi\nss3vrHXBTauRo1mibE2m+rFvp56TDgUAAO2nI5i8w7wNQ72IjJd5IvnADZj8lIGfBXFfdxtgbosE\nI+c+tGKwwffPevBEiPkjd54gze8H1nFe1NiHf76JvRwTxwYyBTTN5MvxQ2IOddALuVK0G3WVcKLA\nqJGyX4qW/vHHjdupwDeXGOl5araEsXkOJrg9TBn6osKL4wnyy7tTG4i2uLf1ZhZ7b9IzvzhE2uXz\ndjiGyL8r1hchK/JuuDnyORjaTMRMGDlm82XjLh7sUzYHvpHB2L/mmfPt2Spmr9Cz98/w70tv3cR7\nOo4F/OLpm9D/kHrb8YU5xCoLj8WtG3wiDt6OkUTUVMPI7jIU4OxbglYipgyVpMi7KbCKRVHIPZdF\nTdQ7etZrKJGH8FG2g36LUGLzJMzmkRr6VCJUV7bCLmUyQqWphmGVAlcw8TednA5pLwXIa5rGtqgf\ntAwUMJ+iQE7l+N6ctYS0lcw5mus+j9c5wgNgYbWIu3qGlC2aHbyq/w0AwK+tXkJnm4fhX5mZMRcs\n38OsiuENfbaD1ctU5k7tAgZHqHB2tSKW11DAcJ9hnsFPx7D9TeLRHlPCLFrjmfcZcg7KtdiW8RBx\n+qqoipnARtccPC/xGZOvMZybsPux8G0y70xkDMC7j+BWWe2DyCmCTc6w1uaGEmNimo+8pUFbSyXY\nGHOitCAYWMIDLSc1olKhQgioQjhaoPCuqCLwFmgs3NRxvdKVAmSjFOJQsw5zJQAAqFaHsbnL7wwf\nEeHuxmlccfNAGq8OoxLl4RI37MJwgUaTOkpjL+PqnhSnkmShTlIBpRTCOFMpYRZRd3NpExUxjF2p\nWYf7AyrPpEc0LfGp4UjQSAyaWjCFeSCpm8CigzxcFgliY/UabicpipO6NCpyGhCmQhyFEpVJRyQa\nVuMxdOqidtq5htakaCyzV0OoRKO1LFqP7tW7zxo2Kzu4s0tjymn46aQtCbblpOmgIwy1lUZOc2gf\n9SVmekbO+vn8qyvQKGkY7YckWC+ST6YvBJANkJdHPVTURl0Gfxml3KhjOxiO8TC4JP0LNDJ8h3mK\nh1M9q0CyzL2U4Ty8Gsrhqx8mMDFLI1CzxXBk68Rh4EeP4mZXSLAi+mn7d7je+PUMntSTz8qKOOSi\nTt+160RO9I6WZmhIJEqDyPj4/3hUhb4G8Zy0arD3LPfNGCad2nEbzjW59tfaBty0kh88SxVIh/jc\nsoahVmXLjrJWJLR5tlATxoavkIHWKObqBpy4pe5eew0ACE1DO8Xn1YabSMcp3xMtGrL+uh/BGeq2\nRkIBv0z0FX/mWeiClMMdv2jIEkrg4nM0tju3TyJxjHLwwogGpqd4zfW1O6KN7tQRNMW+uFsZOEQG\nf/D4LDDJNajEdK7ZMR0WTdS142UNOjo6LrLsn+He7M89FrWNiRdxus3pbAN9I3g49jsAgJkg+VQr\nBwJSHoRzkQbM/5yGfuitB5j5Io3I+WXqqPzk06iUmHgmHbiKyBKz3Gc0OZQ1fMaAqFgI+4DTYl/e\nbrWgfJI0M71jxJ1fp9OkeYtyXHzpV/GkkbKZNwwi6RdXWOuvwazqXh3xOOiFmnvQgx70oAc9+Bjh\nE+HxykXIOFpUomphvDaW9aHYpDU1XakgZaH1Oyhj2GppT4Y+0d/+zkQT+jBDHk1tB8gxXFAYoBXX\niqmhEQk22pYSZeHFJlsFpB20MBMdegkDjQW0w/SCwyUrrP1cQ3xTjZEsw1x3B/ncE5UmkjtMACkk\nunec0fr9AIBiKYPqEN8bCCTRKvNC/9L2m1gSnZ6Ojoiyi6Qd6iNcb2nnCGQJ1rcuWdqQ5TjnNJRg\n7YJRqUHuFK23Bzc2cNRKW2q6OoOglZbrm0V66J8+YQTi9CSt5iDKoZcAALvJd3EhTW/xHdECzvNB\nE5JBWpur0S8B+KNHcDNI25BkaIFLxFzOouIMNrboeWlHB9G5zucG/WVcEM3MW3F6LaP6MnacDLvO\n2PUolbi3qkQ/ml5a2Ok6oyFNtRKjwupevFvDiJI8s624h3PCqt77ULScbG5hZ09MCVInsHqfXsnQ\npA/XlumZN0Zozcsk3RPH2oUyCm4my7Tz5CdJKgW5qNcLRVRIdIiPz3gfyiLxj4tZrdtyGbQBepxa\nVQHNYb5PJ3kIfYmef+E2xe8jpQS1nLjGaDcQEV2PanUN+gxcw9KCmMaiaGMepKknnYasTE87VolD\nmqSMiHw3TPqS6NY0MlVfhW6WdAiH2MJR7wzh4B6vJq6m2vAd5t+t0S1cUtJj1a+SN5wTJaDE6I1k\nJI9n5sU87dUl1Kp83mtxeo0XdFOYsYgpTcYATDLiXrceRdtGPHWifaXjdAILd1l7f2ThDgxPkj4v\nNhS49Qr3+1Q/o1gR9c0umAFrqgrOblOObonuRo4LKuzKuM/K4Bj2RON+b7kBiHBrUc3903gfYG5N\nDKFQZ5HpMPKUakQxXqKHaMtQXlOOfXwkEjEPuovIBBkZ2RoMYKafHddqe/SSDVIN9LuU2X1fHwYy\n5I2IowpZjdcdem8/DmZEG9IuuBmMS2iUuQd6bRFP1ohnQ8wUjtgtGLNxPQ5nHdq88Oo2M/AM8ndT\nJjJH03cUxQoT1QpTV9BIcZ0HVWVITZTP3CQ/UyRlaPv4+ydVeSzFGZ7/nDWMPaMfAFDXkvfyiQim\nLEz2yio2YVZRvsP9x3Hswf0uWAnc0kFYbJ8CAKyY/ajv0tv8XoQ6rG/xORhFNyrz2RS++y3ieXot\nje+eF93tFNzDBjYhF3OqLfFBDDfJK7aJOFQ1ytGWuJbRbQxhUQzImc2O4h++w+uUP7BmYPo3rI/+\n0RdEB8TgIjoHqcNX3r6FSTN5cTVhwq/dFnrktx6L4n8Ckk7n8aOaPi6QSCT//y+iBz3oQQ960IP/\nBuj8tI/x/wv0Qs096EEPetCDHnyM0Dt4e9CDHvSgBz34GKF38PagBz3oQQ968DFC7+DtQQ960IMe\n9OBjhE9EVvO3f/9bAADJgT+GXMYh1qa0EZNLzPB7cLAfTSOzN41BZq6G+l7B+9Osz5r65l20n+AQ\n5KP5AIpLrG0c/ypzAxe0dTy8xqzjk7MjaF7hLFLlpA71BdZq3jxzCQDgWX0SJ1vMML10KodjYWa0\negYbuN9kJp1nkZl6K0Uznh5iBmCqvICnv/77j+D2y39I3KqqTTRuMvu27pUhLGrsjHdj8E0xk7Ou\nZ5aiDEFo7onh4CM6jD/gO2QTi9hl7TqmlaRDPKeDJEvamEwhRBTc0kJoFcESM3vtUWYkSnxF7CaY\ntTc+Own9W8zKXX9Rjv5l4uxyM3Pwtj8He4B0PCox4Z/8y08/gtsPr8YhtfB3NdHSUKtUIVchrdM6\nOdxpZog3vbuoiMbkFQkzOk2pJKRGfpav66GvMOOybJdDImH2ta3NLOKyRY9MltnZqqYFqjYzNuty\nPfpEOkPOxWc1QkbUFawJNmuVaFX5f5kOqKX5DI2d2Y0FiRZ/56lHa7C/POyHSiuGjov5uc3NJDRD\nrMtWlywoepj1Kcl+BE+HmZUlH+v8ihuTMNdZVH/H3sEpJd+7X5IgF2Uu4Yj4fSqXg3ube3HXqcDT\nHtYgZg2juClm6p4MMGt/P6iG5DCLp0ubC5jIkL7r01W4tolnQjSTgbyO73+YegS3P319G/M32eGh\n3Mc9HpXXkG7xWfKNONJ9zNicWwBWnmHtY98mM02vyH1oJSmb4wovWjZmk8qKTWTTpNWZM1zLrWUn\n+rL8LGZtoyAhblaPFLYVkd0tYc2rVaeFVUwAS452kN/lGhQzA2hKmD0firKy4MnmDH7lNx/lyX/+\npychD7EuU9Vhtq/TLMVlMBPXlV+H0c7GHHFFEYk463TPT1PGbm3ehz1JPnrJAcQjfO9GdBRbJ0nX\nEyI73ziQw0diDKt1JAtzhusN2TaguUEe37Nw/2Z0JaSCzNB1Gz6FaoR8XXsmBcsKeT1tNUCyRVr8\n7re+/QhuX3/mMA6PUpYzlhr+4DL10A9/kXrw3Us3IBfZ6u7iyxgdpyy/Xwlh+H+n4tj9GuV/zb6M\nc5EvAwCqdz/E3Aizu7/VdxKj/dxnCDrsnJzFC9/nuwz2TdzepE6UlnaglZIA7qSYvDZlRkU0bnlg\nGEBshzLwmXPHsN5iVcI/+8fvPILbv/rlfqTkzIx25dVoiwEvagPpV6vuoaZmcxVNdQOdCtdWaDth\n9nE/FCIzPRwNw5UjX9tUKSQVoueBq4acaDCktTFTuRJroROi/Eu9CejEAJJ8OQJVmnpZ4uC6JWhC\nauU7qiUZ7FuUyVT/Dprq44/g9F+CT8TBW335jwEADdMvI/UKFZfkvBRzBm6EsmCGKsXaofs6lqq0\nMsfxVEAQ/5QdHT0V6bJHjkk1S3U2fsy/2yatGDTwcJJ8EIXmK0R7fWECjQmWZpys8uC2ndjEQpYp\n48/ITmK1QobbWRxFv4/NJTYu8rAevFzA3sabAICR/oGuuKX2xYQax3kkPBQEeyYFvyjoN0gdkOdY\nhlBpi4LtqBIKDVPyVZk8IhdJB1nRDnuQDJWyUpF0kteQiLGpxr3NGfQZAvx/u4rDYmKSaUaUJjXH\ncSrMg0Pav4jMb5FxhhJAwcJ+p2lRyHAm5YIuxIPw+6Iv738OymQO5SpLSZJEBxJdBcqiOPRKebTE\nVJlUtA6DXoweLPCkDOsa8FR5cIcRhVHOtH7jHlCUin65wtiR7yehFJ1v2gAqNh5k1RwAPf9v2ubz\nVbpNNJRUgq2SCtUKD9BMWwGpGMfoFsPMJSlZV9wiWi2G0xToxgHyntPWB3WFvYTvS1UYa/88AMAg\nl6EmDumslIpzQFtFwU2e+5lODstKdsqZTKzhPTf3sODgd0u1MrQvcD8Na2GsWthEpu9hDbosCTuZ\nJo8kLG10bvCwGJvSYbVDI8ccN2PrIA+loRJ/v18wAHjzEdyW37iG/BDLH3RBNrEIqqRQzlAptVpJ\n2N/knq/7m2hdpqF6b4plP79QvYnvxaiUHIdScK2STz5o9WPmCeJ2R3QRG0uGEe4X4xxDS1jQiElc\n9+UI+SlH+IiHuGHiIHZFWd5G3QmJGC/Xit7DadFkohbluu4XY4/gBQCTuyO4J5p7qHR8V/B2H4ae\nER2+DEYczJBPPsItHBNjK9MpKvqnZQ6MHyA/BaQq3LLzQOnvLMAkxiyqJqiId1shWMf8AICRth8B\nD/lXmV1DfZANHp5JiLItrRoFG2XBfXge7QgNtVaiH7eOE3+7OgPTUWEEfutR3D7zNQPWrlCWG3YT\n/sVLNMCufMhymcyYESfeJL/IZtbQWeChpTRtY/8XqXt0U+Q5084h+E+xi9NbI0o4JcS5750SNJuk\nu0pMCzOtLqMR4mGqDl2E8vNsqKKNFeF4QEcpMCR0zeflCL5Jp8LqGYHEzPF9qp/cxqWnFI8iJUBq\n0MMtGt0k+ypwGVmypc7RwHaqHQjqRNc+jRW1Nv/u1xZQE73oq3k2CZmYHEanJKaIFZywqKmPMqYG\nXHo2ulAm+K5wKAqr6GInadhRKZGXh9wDqOooTwojDc9GKgl5hN/d1ZbQOkze0ezLkXPlHotbV3z/\nP327Bz3oQQ960IMe/DfBJ8LjTbdp/R14LQq1jNaqJXIe//QSrajhZ/cxtEKPYvYFtpz74PUVeBu0\nZNoTOVR/wnZjBybdSMtpuasmPgsAMGQrcKlYpL7pbMD4Ib3TVLaNoRotbNUQrbw3Vuo4YaOFHo46\nMKSmx2tf/H8aCVhStKwiyUFozrFF4EZa3RW3joKhtc7WSUxbaE3dLhzEuIOeZbpvBHrRJCEhJixJ\nD6UhWWD/W8/5AwhF6XEcUvqwqwoAANQKeurx2hlMT/K5EVMS26BnMLF6GNYR2lWVuLCv9NdR85Nm\n9bcN0ByhVS4rJaC00Zo0VBkyadxcwbVf5WcH/jyKn87e+I8h0VGgKTwFnVVMS0oqUFfQq9SqamiI\nnrSKiAYlEcKHlWG2VkyCSINrb1RayNKRgExXRVLMM5XviZaOUhM6cVr7BVkLzgrXZqnL0BAtFOM2\n0VYxq4RBSgu0qsigWaM3qdEZII1xnSXRY7o90b1lpKffgLyKXnF7gWJy9EQEzVV6k3ZHBbI4qXIG\nw1gWHoFLzLFVHC5jLMpGDM2FGZw5T/5d2/8snlAx3Cd1siGDd9aL0eRPox46hFp8n/tcChM36Kks\nHidNTe0UZP1iCktqEN5jvHJQBSvIXqF3lm6TDhOW1W5jlCFp6jAnetl+P0E+PKAdQ0p4rtb1GWyd\np4z49uZh1fOKpCxmfb9RlOC4jWHTaxk/jo1xvTqVHua3+FxtnnQt+NQIi+lD/bt2nBoUfZn7luFa\nI1/fP8N1l+Id+CzsC/11Yw7BCl9Y3NJiZZS8Y434+W9otgtmQAleFOP0ho6p6AnG6iYcjtIzu+tY\nw/ygmDP7Ix1yZ0krT4hy+oGlHzfkfO8zgSYcPjG83tSHc016gO+H6DEbpAEYcvT84X2AC7kAAOBV\nkx8TTdJ11Ui9UC1nMTHCd22FK1iwkA7nZe/DGeeVw5DEhkjf4weq51YKqIuh7lFtHyQl8pduiu84\npFpH/KunAQDK/FMwnCd/utdkGIzzu9glH0pjUsQy9HhPFn4VCyLSdfzlFIIbpLHKTZqfXa8i83kR\nfSiu4OTf+xxx+3sGbEvp5T9RpL5SX9uFP/QM3zWawNLO9wEA//rgFP7RJCOGn+mCm9ZqRdNCeXOZ\nzHBLxdWKTUwPk+bgVxL3QtAI+zT1dkXtgTJAb71tFf277VIYqoy8FN1VaCu8RtAVAFQDAADzTyNm\nZwZhUlK2Gs069AnyYqFugewMaeZeZJQl2FdDqsmIxPBOERIl+aDjGIeqttIFq8dDz+PtQQ960IMe\n9OBjhE+Ex2uvifZe6gyCfcJ72Xofsy/Rm/Iny9g6fBIAULnFOzn7sT64xFzN0P4qVLNfBADUcrvQ\nay8CAFak7/MFplNYi9GiMw/1I5JkI3H75EswXqfHqj9E68Z2rYrmDr3GdvND4DneYdbaSUjFfY9a\nRo9jVP8TVKpsc1bx/U1X3GQJ/l5ufw/5Gq35Y4osKqK5uiGlh/EoLTnNLu/dVjMqHHLRQi/WDTgT\n43vvPFvEYJiWWsJCS9ObjyFZo7f1xL4M2RKfVRyVQrtMr0M9yzuK/g0vLpuJ79RUHrp36DU3XEC6\nn9ZtQkHcZQ4Fjv8pf1cZM3TFrSSNwdzhfqj4KEiUBYRF+8SyUwJ7nCxWVidRrIgBBSl6Ea1sE80O\naWlUVZHV0hsNJuowZYjHT+fUqrNNFA10iWuyBtpVfm40ABJwDYoEf6/umKHR8F11mRQdM73fdqOB\nlpaedBWkY22r+wQfV7OKoPDO7FkxZEKbgc/BPXLKnHCJSU/bMymoSn6uZ1okrCWH0PCx5aZEsQXt\nHj8//Klt3K/w3c4iJ50UzbeR3mI7vRddw9hZFxNdDC0kTpKW6RLvmS3uEkZvMplmQfkAhbCYjlU3\no89Hy327yojPkqa7eFcHm5i/yUSVY1K+K+G7iyeungAAXHG4iW8AACAASURBVDqdh6NIr9A3K0c7\nR0/CICHPlaZX8O4lRp4czvuI3qcXkBsA6sP00DdF20V7ZxtTWXotofMqqML0lPOqPhSyxO2YJMB1\n+6axG2CESR3QYP8499PTPgKV5BoAIGNlRGFC+t2uuNkH9nDETW8pv0lv1HZqHd/uI4Oe+lML4n9I\nD3zbbsfgA/Lippk8NFdJo36Vf285bEjWyS/Th49Ac59TGRwnxFS0VwfhGucdek55EBvX+AxjW46w\nmAXum6LsFFd8qM3xu0dk/RhbExOUptUIavgdm1KPqfhPc0XefgQ3me4UHCJaMhPzYPkE5eELPyHv\nJGBD7Dzpd+nOh9Ck6WFKP3UGixLy4sk+DiqwHvoTSO7TM1X0fRv+pS8BAAzSeUxk6CFCyTWWDKOQ\nyej15aZn8N73mDDl2JrDV2YYrfvzFNcwVkniC4eYoPTALUHSIObmvnoTkT9yCkwebWRaspkwKeYd\n77TzqKopl317xFEzqkZqizzlmavBk+ZzVzoBWIf53GqNeTES5KBR8bsquRJlDaMIOq0HCjEUJdem\nPHrkeqjFLKh0vh9qO/cbdjOkq2Li3SHyfydoRaVEvS3vzKEuEh/LoctQtI89gtN/CT4RB2/sXSqM\ng55lVMokiPyYEho5+8EuROqoX6UiqI+LLMzFKuID7GGc3dDhqItJL9uF41CHGGDTWakoivkd3Jvl\npfpTy0m0n6awyX7yNvZ/g9l+ilfI0MOGZ6ErMVMvKrmL8D4P/MR6BMc1PAD3GmSye5qncSRMJpKV\nXwJw6RHcMid4gNg1ByBdpNK+ASPOiAv7ir8Mh+gtvZdmuOLJ2VNIK5iUkVquYtNDQR8spiGNcoPP\nmrjpFh3wA9Gl7IwqjBUrw1ZauQbqCSaUlM1MoFmQ7mJA9FRem7fCYyR9TgwmkBAh45iNymFUPQOL\nGOIdPx5+BC8AyDerUKX57pCOh5NG3oGyxt+VMmVUGlRi7YIKIxrRq7rAMFFDVgOE4pdWs5CUefib\nFGpUNSKbMc/nVkwSqBr8fb1SRkfPg1XeKAJy8oSxITIrm3Fstvl7674MEq3ow6uoolLj5w21yHiN\ndu/wVvCY4H7Iddr7uYfqfQf2LAzVj0qqiLso6Pl0FhNVhmNTqzz0nnQbsd3m4eYdTiMxTjx3FVH4\nfCKj8ib590hLhZX4rwIAbjduozTFPRxU1VDfZFBqtEHjtN2YQNRF5aoflKKS5CGjzS3BkCat+uUM\nie70PyZxTHcdgQxla9LGd726ncLhCcrQExEn2g6+b3/3rxBz8MpGXeehWs7aUVfREDBlgbyPdCoZ\nTbj8kArv4IuU1/T9Qfyww2uesYQTpjbDc+68A5ovkZbVu2IC09gWqkpxNaHowLjDBDmLch2WHSrB\nwFHiviomMP3nIBmoQ/qAylphYoJX0urG2dd4sNz5+VtQfqAX+KSwmCXPDUyRHzJXbFC5KAvzB1fh\n3SPuK6nraPppDFuTlP+tp/qhD5HWxY+U2Ps7VODtrQYmazxAPQ7y190xH0bmmWgUdSvRdlMXnFZP\nwyQTk3Su55E5aumKFwBsme/AYyEdSu1L8MQp1/9nnYbcE+eN+JMID82vGoKI7dOQMlQscJV/BQAw\ndO3PAQDrA1NIuV8hfd/4XUiPMSwdeBjFW05OO/rS57mut9fz0G+wB/dLxQ0c65A+lZIGyV3yckzB\n65yhh1W89UXujf/tBkbAPbCrTuId77DA5MojuKnrWhSMlFNdq41qnDIHHw9VRzsBp48yn87a8NBA\nnAfiJpTm+H/dGg1sd6kfCbtIzLUXIcvwTHG1pNjPc20mL4++ZrAFjHCvRlNNxM289rSX9pBW8vDf\njxG3fksH3ix1ZtK/gWSefKtxnoDT3Uuu6kEPetCDHvTgEwufCI/3RZHKvqYdx/A+bQFlroQHaTHZ\nwmTA8VFR71lj2KBa92CrwekRk94V5HO0POV9G/CkaKm8paMF5bmcwKE6w8uhohSWh8JDkhjx3g9p\ndWOS/5paN5Db4xqKQ0a036PlLzcUcL3B0I22+DMAAHPox2hIGYZwd8/RQd9lUV6iaaM9x5DS+aAb\ndQ8t7TnnQfzLDK3YZ56mtdu5sYExK5NH5OUEksLyMqw74JXzu9EAvZl8Xx9morTwb6jaUOtp8Sqs\nEjQ+YqitImpeT8+qEIrTCm5OvIrkCpPFbuQtMEzTqz06T4suYdRixcXkF++uqStuxkADwTrxc+pJ\nAGmwhbxZTEDK1SBJcL3OPhVWLbT+HTlRLyptIlNmaCdR08NiopVaCzXQoSOGqonekrzjRFZJdrW7\nyijt8gttuRyyGJ9Rd4rQT0MKbY7emVxuQyPB/+fdDlRbpLGjxquHXUu7K26HlHvIDDKcGkoz5GnX\n++Cu8PeliRRKSYbiRicGsBMhDzuEJ56tPUTNLbzpoAE6l6j9DKRwUMIkurfHRLLIvV14TzLRpR2f\nQztDXg1f/O/gvct628os+VMaCyDezzIc2ZoSZgPpk3echaOPCS6JMOk43e6e8HfmJ0/C2s/QbaNB\n7+WYzIWSllchu9IOjGquZ8s8jadjXM/3opTBC1IL7BVROiMvIjzM9/geDAJGJsDthfhZqKjGYTnX\nrp7NwvAm995y1g1J6ioA4G6bdJhsjSHkIU0/UphgMhOfcnMajmHSb2mZe+Fr1rritnfPAd8Z0j0j\n6pLHY9O4+RR1yeSDQUSfYZTrwq03sd3gfurS5N/L7gqOeOi1n1mZwqKXYVWDtoaOQtT/izr0px/e\nR9zKSNrWwDLqy+T7cw4ddgf4bm+UETHXRgy1M6wfVl/dR/Jp7tH8mw/RnKJn7zyYQF6n64oXAJxN\nSSCVUX41D3+AoIgKFc+wHvePVm5hrJ/llqcNOXznDJPMSrt5ON+l9/rRLzEyo9SpMf19PwDg4IW3\nsbVI/GtnXJi7TLpLgtSpc/4X8NI18nVVnsBgitG6u/o1bA2QFpoT5OnJ8TqUAfLUq+N1HFoXkanh\nVbyk5pXDH3fBbaQpRTjMiJVHb0TbRb1RT1A+TRobAkoRCdLXIRG130q9DrkE6T4pEmQb8jb0BUYw\npNkqGj+t+S1l4PCT1uY46R9yP4RRy6uSsksBswhhVzUS6HXEX98gT7a3UshLRGlnfQQOKfVOoR+Q\n7dq7YPV4+EQcvA8GKCiaexLkhoiMqtjAjIEEO5YaxrKdIbySlwT1RnNwW6jsdu9MY0jLQ+3O6psY\nSvGgeM5Ehbt68msI3WMo5fyRbcjavH8JSSvIDDBk1lhkOGHUG8C/k/HQU5acODrJ0Gt7Twu3lEzv\nNDBUEj14GEoxrixb9XbFzSLCK0WLBoZ1bmry0z70tV8DAMxfruLQV7jB4+8zzBbPaFCZE3cbzhAk\nNTJvKatErU0mkVvE4HX3fYTkNEBevjuEtREKY70mQ+JzVJhDt24Q3+pxbIi6wtnmWdgnaTTIQg6U\nfkzGic0RD5tEiQ8L/Kyu83fFbb+6CYuoR24XREMPXQ76NOleqSlQ9opmBvIEdBnuV1FFIc+W2pDo\nqPgaxRLiVYZNa5YW7GV+bm+S0at1GYoibJfMmuGyCcEqWFBt8XctBZVOu2mBSk2FEG0UoFfwGfJK\nFbos19ZQ0XBRVrvXg27vnkB6iOHSsQFeAchyc1AVeb+aKz+ASWRTl4tSuBo0boxt8lO4PYJJMbIv\nasjC2eH1hWKmH69LyKvuEg83iWkYyy0qxkOGONpHSZ++eAEhJ0NfShE2LRincKFDHKJSF64laSSq\nlBVEajS6Ruzc19V4dyV+Y+QSwjre9TWHeGdV2YjhSoXGoNSxC4eTCsq+6cXKIN99LuknDudk2AlT\nhkYe1DA3z/d8e+wSvtD4JQBAfooH80AngmaN+RfllSLK0gAAYKuxhUMFMVKzShy3dW+gP853DPzI\ngr2XGfKM2yyAjnrh+AD3rX3J3RU3ac4A1XXu6aqcGb5BxT5mxHi5TPEZqN7mga9QuJAs80BOZ0jH\nEZUBorACpdJNeHKsv84FPkRNR5o4zpDndy1NLN4nrW3HdPCI0Hi2UoOmwbDzTSEL/tNn0QjwEA4/\ntw5DmQfgzvMyHCmSj6SNOtS+ta54AcDdh+MYCpHP8v2fxvgyD4Qz8/xs7XcscO/wUIzeMsBQo15Z\n2f0RZF+mfPrLoumLRYf5498AAAy15yFxMNx6M1XE0UPkg3vfIyHuvbSDlugJcEyvhVFcQ0v/RR3O\n36RefWmPDsrW9tegFFULXwmdhH6FWc1vvGhFdP79x+Km1CnQdtKI7Oh9UEeo86TjNOQCpUGU7aKG\nuViHoWgVf49DKiEfbYvaf6tBDmmaR5tB3obUyGftGidgyFIOm+L6SZLXo9oQ+SIaC9L+ffG7GupB\nMfJUKXJWDEPQVfj/jruJVooHvjSoQ8n8+Gz0btALNfegBz3oQQ968DHCJ8LjVddoWZQOlpDcosdm\nsB1GVM7wp6t8A8kJeg+6Jf59S6OE4Sa9wjmrAclphs5OmPpwM0oL8GiMnpBzaAl2MxONtrUm3Bet\n9X6mOgb/m8LjfZJtzMLJp2G10KN9fv8iFNP0WDvTKmTyTIYJZOkVmpurMI3wWTZ5f1fcVg30DM5U\npAiLNog78b9BJE8PW22Ow7vOgfQlkXlZ7ZNBFqJHp9P3Qani78YvypHsFwPiQ7T+rA91eEpDqzvq\nW0TDRU+vmfHhQJCe1ftxegdaqw6Dc6RfJJmFfJJZjZHlOPonSKvDVtJxsT4M3T2+w/x098QBg6IN\nTY1efKcqMl8LWsArMqNVVbQ79OQy1TrKLYaC7Al67TVVDuoy3yurtlCPM0SVdmagaNBKbcv4r0yu\ngrJGD15dtyFVYDTEYK0DCuJkLtKql6CFco3PMsgqqOgY9tPlpcgb+T6dnDSVKbqHLE3mXTREVyN5\nh3uV2aig/BK7i00vShAs8/NGywBnnc/JP8v1urYzyOS4hwe0dnRELbX04AFMZBmy1O0zOWb5+B28\nHGSC0nJeDbfoOJQazkAxw4SnaIBhYK/CiM379Eja2iKcPvLXwdoRBDyMZlxapgepCnUfcz168yRm\nXiSPS94hDif7wliWiiuNXS/UefJRu5LH8gLDesMuev7//i0lzltE+M1/AWlRc31KM4c9MRD8zD2G\nCKNjLVR2mFGbNjtQPcg68XHDD7G+zAjGucP8+/71MQRF5KD2S1LYU+T1/BvA5Am6WZsqUd/9rA/4\n4FHchibqeD/APThwhN7s7u0grmiYGOXQXoZbDH1/U5uGU849nlfTuztXcMK4yGuIgnULnSl6aWVb\nBY4meUp6nwlX/pHreHua+/7Uh4ex1CFvWOIqrB/hHpZa9ARlD+YROU2efcHswlvgd4fnTcjKRP30\n2AE8yK8/ipQA+0QM+3k/AMBz6nW8N0CeUQqam//Br2P99xgaP9p6APUtvtt24ByGhxltyn1HZL4f\n/2uo7jwBAPj9U+v4YoayM3kijXdivMr41M8y6nQheBNF67MAgP+jcRO/FaHHv/W541hdJo8p9vnZ\njc/X8OVVZmRvy5NYFJ0UJytLiG+fEpg8mly13tRDr6KOjwRUMBtJV7eU0cuaKgedCB+r5X0wGylP\n+YwbTpHspXQxGuLeUCMAeq6lUROkS6KTnj+NdoG6W62iDFlagEV0s0tVN6Atks9a8xWkJshH5io9\narUO2HdwXysBK3Re6mttRodc8L9qDO/fwifi4FWIDMsJdRY10TLtwt2b+GCCdzFSfQPWbRLK2yRT\n3LO7sDNBReAM2bG7yBT2WYUWLiuZTJYiQ0v35+E9J7LVWjtwyihsf75axt//Ej9/8z6FIvIghupR\nHhBbviLMImtUciaOZl60NFzkpruLOdwXylkt3e+KmyUqGifUiojEiNspxyls7zDMqDmjxQnRlvKu\njzg6sleQaomC/2gQn/ZS0LeC1+AR1S+xEBlSWevgFTCc5UnVoD/C9VQ0OWwt8+CcnOKz0p086g0q\n8Kh6H6dTvMuxvZBHc5sM15QzVHXwxhKsF9gLV/nKD7viVk5KUXNwQcYmGbKpbKGhoxAa1/JQiezr\nhkoHkwinrmm4xoGyAS2NyJQ1agEpf3e4o0WzycM7I/oOp1N12FUUGqNSjX1QKRtUgKxNps/LeVhI\nJDU0fho2rZbQFId0w26CtUSWVzaotHLN7kGfzUgDHrHO8AaNCu3FYygtiex5+yRkCSpwk7mKtoGH\nU+uqMBgafshNPGCrHRXCI1zb+OI1yETJVlgojJl1OaJK7mf6cAj9Ee5FbTmGqVnenQ3pyYd3tvvR\nFL1jO24r6gUahouaDWgXmG1rPCqaGqhceLWLHo/MNtAvoTF2Q/DcV5HEg8O8Yjm630Zxk1c7+x41\nfKM87LYrNNTm5AlU/RcBAM6FCAb7uW/LrRqqL4rM/Xd4v9guqmHyUPG5EsvwV0ina4tn4D9Nmbmf\n4kGX0ZvgVvBdrbsKFJ5njsJ0ZxOrWn7n4Dj5IXH15qOIAbhq3ITawzBuVWRCz1j0uF/gGnx6P/xy\nhs7rSSf+WtTBfXWAB09r6y1sneT+tKrPoniXf/c/O4xMmLRSZnjvblhYxC+P8HAaH9tBNsiDZa90\nFdPr5K8lsjxGlTpkc6Rv8v1lPPkF0TLSM4J7Pj4vLUvj3D5l9g+64FZoDmNC3KHX3vqfoRWNd/wg\nzx38HxK48n3RHvXOeQxf/McAAOO9f4hYWeQIDHHfz5WexiuC9Q83LFg+Sn2kCs/iyDb36HqDB2RC\nfhFnT9Co+7mfbCH3dYZblX/yHE49+2/4nczPAgDG3s9C9hIP/Ni/HcHEAHWbx3QCbZ9oGXn3Udy0\nijbUUuqCplUPuYL0Ww3yMJ4bUUAhyhAzkjhiJsqeV2qEusn12EXuyJY1BXNRXM8ttyHv49/NqQ7s\noiNnNsfzQtsvQz1FPpGUVGhO0RGrlRRQCl5tNwYE/bNotymH/fYCohUe9NKyAnX3T0ul/uugF2ru\nQQ960IMe9OBjhE+Ex3v/IM///VVgJEbL6+r0SQz83+y9V5Ck13Um+KX33mdWVmV5X9XVvhvt4QiA\nAAmRHFFaaqQNSaMdSRsxMTuadS+zETuxMaLWzIx2J7QjUWKsQJEURYIgAMEQQKO9767u8jarKrPS\ne+/34btQxBDZGzsvDDzUfemK7Mz/v+fec8895zvORzgrXPNjWy3yZTeoAdXXgzj9LK2zoCKNGREG\nezu8h8PrDFDYNtNiDsYBwzvUTspHtUjXaTkd//UQgo/pFJeJQtnNyiAuiOCVu6sqmAWMObnvRV3E\ncywaRL5Z0Yo9JQMjbAJ6+8VRHxUwaHUMAx0GstgSeqQDhPisK26seKlxDa1Rw3xfO4a+HC2Onol+\nbIjIXs2jPmSq1L5CTmrJL6t82JFRC47NvoLSCi2DorSCgQC3N1zn/4+sx5EpUeVzDBgQFME9jZoE\nPWvU5p+MXBDrkcX+NmE2vXSiK21ysw7tKtdVphRF7GU5aETThpqigaQof+iEAsk897nHKJoDqLIw\nimIkUnULZTk/T+0robIKqLhGa0rfr0RURI4rSxVYRFOCVl6BRpF7pxLdnRptFQwmfrmo9aFeYwBI\nPaWCTM91LYuiI+l891zXl55zYuEaA+uqogykaqWEyiR5Z2BjD/edtCKaWx14RskHdgf3UnUzj2Ke\ntMeO3YcXtN7SzhG0RICXSkcrYhcOnCkRYs3prCjpaCbpToxja5nrsNvi2jh6LqMKBlG18w04Gwwo\n29U6ERulpfflZUJyb1aKXWmLTo8gNc+9GJcSYk3aLuGZFPnsyZIR/iOE4ietDWTu0YIB45Nw4pgK\nPxFFNWT/aATW/H0AwKWoH+U8Nf+rep6HVAtA9hIA4PbbGjQu0Np0qzdgvMkceefLXMelUA1yUe6y\nHqxgYJ2m0QO0MfcO0YdHCiIDcn33NIJLtXE06pxb2EkajM0GfB3SGx2wox3kOWwozPgnHvJDdY8y\nQ6o7DrmMLiVbsYzHA+RrxU4FgmVg7NDyutE5iYE7ogGJug2JlvUDFD47KkqiTDNl8sDPT2zjmftB\n/v9zwN1t8sCYaQNHH1CwtIdGUdAPCko+/hxtBV0YkQ8ZKKj9zj24/yVlQf3XuabvJl9GRzRJ+eCb\ne/hShAiFLnsV7QxREHeA/6aPjUNt5nl5Ru+H628IfatfduE9I8vvnmjw9y33PlKio9bWxGvIXxXR\nvqNvI+j8EwDAczPfBgD8+wrw229dAADs/9d70NwjghGPrKD/G8xrx88+RxrkhgyMRu6XNtpGwUK+\ntxt4/pPJMlxSyraOrg960RwkUmigIQJOFX1ca1epjZyEczRPtlEokeZUawehBPnGZRDoRbQGtZ7n\nxVAYQOYxEZuUVgOdlmculhCdmVw+WJZFV7PBCuohkbFhTaMg/3yHs/+vcWDxHoyDcTAOxsE4GL/E\n8YWweMdB35TJ48aqcGSrQtu4l6cGrvdIMCi0Ft9FkceLLBZrosVTLYvYrvCXaRtQSL4JAGilfgAA\nOHdqFmEXtf/kz9wYGmIglfbuDBY7tDQM7/D38f9CjeICLZFRXT+SIpx9Ey3oRT7t80u0ku7ZezEq\nWtw5Ta2utOWTorWWsoayndrbgrkCd5aWXv9ECJt71L7m4/zs2FEf7CIoq6DIArvUTI8f1+Juln5Z\nd4za7ge6MAIpWtXbhRRWQe2tf6YD9WPSYbhITTOx6IJ0js9ty/Q4eo1reV09heUMw+zNQVGqztPC\n8xGuzU7b0ZW2VnwLLSMtvWqR6wRlGTErA81cVhlMBb6vtO6FTJSlrAdp4UjsUtSL1BTNFcBmEeUl\nDTXIPtMJ/aJXaaGA3gLfUZabgRbfoZLGUXOJqkOiJKWjXkWtxP3wQomCCPvv6GqoiACNTo6+mraq\nK2n4NGWAaepbAAB5U1Rh6uzAcZ+/W7kohyNJrfv4lA4N0c6uJCrjpFGB+ngAAOBb12NLVBHT7wwi\nqxA8JyrqVD02/NDGtelfd6MwQOsutZ2CscF1MNhFf9L3zkMq4Xy2hxqIqXgG1IUW7CFacvMJro2n\nv3tQ3NDiBkqiPVxpg89dS2bg0ZOvpwJ2WK7wHe2hi2haybeaPQbu3NHo4FcJa0txDckKz+y96j6K\ndVoB63by5KWmHhDtLmd+qwLjHq3ymu06KgZa23cfEc0qqyx4TUE/aGmsjqRI8wiu7+OVc6Qlu0Be\nLPc1u9IWaUthldGS7q8R0fl50oUjCvrmByPjWBD9W3P5HchEr9blTfLIcCIFg5pI2sJUDuNRWqPx\nziakolbAhoijfG4eSBh5NmNmF7wDtNAfzncwJnJ9F75GGjXbTsydo6z4/htHMOLj+0zn76P2LZEy\ndmsfnpWn20LnFaN48E/5DOVfjEP/e+9x7j9gkN6c+X2EqkQX0s0QJg9xDm+MhvHVJe7XdRWDJx/+\n2Sj6XuK+vtW6jdPPsyJeW7uIseNM42rnaN0l0yH0LvLMWnqrWCqwyp/rZxoUZmmZ/69yomK9mzto\nfJOIzI1HdiguixSq3o/RG9x4Km019RCaeqIOZZMGZocIpm1QbkdbZcjN3PtWLo+mhHNXWLPQxbkm\n1RJ5oqWoQJLm762lDEJJogR9KisKGtIRs3Nf/G07Gkn6e5OaLZjb3NzmXhFFM1HUTpWIAkpxhE2c\nw0S+gbyPvB5p90K/X3kqbd3GF+Li1YFMqJeHYDMLWLV+Gr0h/l14VEHZQAGxbyJkp+jsoT9MSEhj\nM6Lk5MWxr/86zKIRR3+HgSnhrRIQ46Fxq+OIKVn+TFLIQG4ndLg0SDjh1FoHH4o1/J2iF/ko8bWx\n6gx0dQrXqouXiemFLAofMsCr2vwMIvpPR81MSElaNEGu4neH603sPaBw/Ukhj1/xCobzMO8w1LwH\nQ5PwZiolgyJAxWQp6oBDy2COfVF20e/oQ3qXF+ivDC7gb+IiiOLaIdQcZJz6LmE/g1YNhYh0zdXb\n+OA1BqGFP03C/gpZofA+Bbmu0sJyH5lbLbnflbZStA2nlBdGS0DG9awMPQbeZrlsAxVRFMNk30G7\nxo1JDfDy0iS9yMgI9ZllatTTfIbWrYOsyQtMUQ8CAEaLbUSkhOdrqjbKRf5O2ttGpczL2yZKGlZK\nVahEj97d1jbkQrlqp6SwxTnfjJ6f1evdS/Q5SxLo+gi1p39MQX3EGcEnNlEr+IEHdimFZN3fwtqi\niM62iUv1xRoMuywpeb1PAeWe6AlaX4evLei0UoDpy074lykoas8osfVQlNmzOVEMkC979sgvty/e\nwMgeBYW+vQ+5iIiNGgyonuI6dFbf5vNN3ZtzNyrrUIpm8UkHn+WS29GpU8iVXBLkKi8BAPLZOPwi\nGqY5x9/4ygm4CuSXRriDlSKFUd2lxPky9/u0qPUcNo7D7+ReFMp5HBduhgeFw9hs8mw97w8AAO4V\nTdg8ScXStGBF5iFpvvTlIlJ3uWYLI4xsD3i7a0zDJTUejojSokIY1kxOLGnIe4fcx6DQXAcAHM/X\n0BRdlDxCCbhV12BiRmQOLBfw2E/o8cijM5B/mTKms8Z9j5w2IymC6raUBShrDK7q+FV4AtK/tsDP\nKttv4bsneKEpj4eQrVCeZe8U8esmfveNig3ykUBXugCg8ztR4A3yVGXoHSRviahbq9iLZ1zoqOl6\neHXjDh6aWAt84r0orh2m4qeOUCl5/sg4HmZYS+B1C3B3gEqb4uYo3F+jgtVcpsxUDQTx0e/yd6/9\nTwpsvMJ92XtuHY518qdRwRoHv3u8F8F/y4A07+APUf9nVKTO/sCNmKe76wMAZlQlZHd5tpRZCRo6\nyrSIKKBRcRogi/NspZoyeOuUBXZVB/tWGkRaAevX7CpIxxgkVS+pIR+mXEhsR5CscO4+EZCplCeR\nFO7EUqcf8x2eyTmzARsJKvq9IhulbJRCI2q9lxb0sNf5edaYgczY81Tauo0DqPlgHIyDcTAOxsH4\nJY4vhMUr6VCTXlAMQ9pgUMJe4jHMoNWj7R/FQpJwWkYzewAAIABJREFU1YKJ2veRRwHIhplaNJ3V\nYLsaAAA4wnfQUvPzoI0aiU5bQ0lopj1OORbfZvDK6DkpUku0GIynGZCRjdkxKPq63qnuQGqkxpbO\nZ2DWUgPakxLaUeTrmBVaXEjZvTyfWeSQxos9mHaLqluPUljt5XwuBg4hrKcW71ygxZJoDWPDSK3R\nt5/GsoxW6LI2hUuiTKFaSthm834POnJaHH9r0qCYowWvsddQ14i0qhUGF9ndAciaDE4pzAfxQoPB\nCpvyXtjLtD4KR0n7T4ttzG3xb/m4oittpmYEq6JIfL9RNChwpFCPMMCm1ixALTr7VJR2aEzUWF1F\n0i4zZtDIiAo0nirsSc7NZFYiJnKXjaKjUxplOATsWjGkIBEl3xRIQZekFWuUilQehwqdMueeKSRh\nFelj9eoTFET1q609ztGvKXelLbcaRXiVlq7pS7QG6qpB+NZ4ZKx9DSjCAuJfNiMiys5N2TmH7Sc2\nmNTkM9UnLXheIJ80ggY4p8jXt5eYR9k/WUIlyHcpIhlYRKnJskwBZYzzzAu4tjfWj3UROFbZd0It\n0oH0NS1KUe63ScqOWf6wHt2SXTe0FkyIal/ZCFEYe78OMjkhz1RjCyot+a+ityOamhXrSuTjVKkP\nV6bI73P3alDa+azBpgM7VlpA+RznXZE8gb1N6FY6rMa/uRIEAJw7WoBeQ0gysce9Oo8OSo/JA5cR\nw5EJEUzzfh0GC3nGLRptqCPd86+bVicUm1x3T55rozvvQlY8V7H6J8iKhhUf1+eQkdKyGtqmhTR6\naACdR58CAF4z9uPHUp63t/0JmOZ5DqdsXIcliwa6JH/XXsvgfp8obyp3w+fgPDt3uCcV3VnYO6I0\npteGh3XO8Zi+D2/cpSWtH+yFzvR0yLLzH+2o9HL96jt6jDR5thb7aaWtbs5j8jwbMdzJSjH+d0xn\ni1wswzj0LN/hegcAcH8vDFuF1nMmvAaVSK87jnX86YeUc6df416ewyv40Sesfld5/TycMrquXipN\n4UM1rfXZZa7ZHx0+i5d6GD1VjtvQp7gMADAWLmBJVn8qbfcqJjjzRHrKfR0kRVc3Y48ImKxYUIvx\n7Mm1cUT6uQfG8AjkVe5R3Egr2JHZR7rK89goS6HukD9VOhf6RHOPHCgTtsJxxOR8h1G6iaEG5dGi\nOYHWHnlmQ6Q2DVQtqIj00Ex/CPI6EUVl3ohKz3/eVfqFuHjzDcJs440iEsIXllK04E9wek8qVRht\n9A29WuBGN91K6CXc7JteN+pBCv7VQgATMwJyu01hZzZ9gL6eIwCA8PIQvEM8ILcUbgyJesQQiemS\nXAHNu6LzyX8XxvAyN62ojmNVyoNntfCSWt5XoxQTbQqHul9OAR//Xyv7S/iTvCDvKYdha/BAPtmv\nQ6YibOrxkRkUkSicw7xYdN4ADocpgD7upBE2iZKEKv6/fyOL9QFRwGA7imhL5FSahqGXkaY9ByH3\nR0+2cHqO0JnFlkKqSHhoufVjOIws4tFT4LNO6cMY/AoP5v317rWat1WALE76miaRzB/VowlesHpP\nAdUq90Uia0In474Y1bxU2wYfPGYK0ESqCkMPBXBeJseoXKwbyBt6iQwFUY7RkvehI+PvNGkZWha+\nuwMRqVhWACYqUr11HZplrq+k6kCkTv6SSvj7VLu7r7Cs74VZlD0c2hBrrt2Hxsg1fWysYnhLCHO0\n4TvB7xRT/H9JLY5ilO8NnlNjcp3KYO51NTY/JE9NmEWbw3wdcbfwQaq0yIgLSXmvCsdpKhtLWtFN\n5UEWMpHEn5NIYChR0WpqiijrSL/BwPWtyJJdaZtOjmJ+msKqx82IZcW1JOwneLbyZR9UGVG+c2oK\nuk1ezgqPqNFrL8Kyw//fM/RA4qewqq2VYLVxTZ7tEMIuBNUoyMjrl6sKXBjjhX7FoMHU90h/r51r\nsyHPQ2kk7/y2VIe1HOd/+7gZD64QLpRoOe/qendFt7AbRXOcAt6Q5XwNP7qOHx3iXsrKDihXLgAA\n4qFNDO1R6fWMU9kpprewVWc5zdb+bTh0okhCWIuogn8XG8Ldtf4uhsfp23TYolBv8rykh9pYThKu\nTenJF0dkR9Gc599/M5qHf5tK1weTEbwuWqE+KM1C1qXD2WfDkajgwjTP8numG2hmyQf/rZrz+Vf2\nAErXmN+8tG7F0Zd5ecWLfXBc55roVP8IADDk3EDxsIDJr57CwAah5Nu/dgt/HOMFeFsk+l4dGMG3\n0uTJvP9daK7xd380tInfC/DyiW78IQDg682/hMRG4yk8cATG73yH7/0v9Rj5ydMBVr20gJCE8iFf\n1MO4T5nnrJPvF5RxBLTc84LOAPkq/y4Np5AN0bgxV6kotNsDaIBro1PLYBbtBqMJBSTCJ6/K8/+T\nOjdsHSoa8SrgTJG2prMBhZ+87BIdx+LaKipuzlFat6NdoIwymbXQJzJPpa3bOICaD8bBOBgH42Ac\njF/i+EJYvLIN0XRg5AQiMVovtZ3nIKsSIm1mfoCcmtFmvaIU3fefseHknVcBAFuOBupeah/fuPIx\ngm6ROyqhplPU/RMk5Zf5rvYivCLiMJR7iN4WHfprckJODYMHjhlqq2fTz+C9j6kNnRhx4vEAYaDb\nYUb7/cHpJm7s0YLyCdjmF4fBSI248W4A0pdpkfj1EVREQIrJ+ynq+6QtOkB63ZMVZPZpQf9k7x18\nXUM6XIstbKlY5culo8W2qPWjVhe5Z/EGHCPMXbZcjaFzSjRJuEGNMNnTQXKT2qj71UlsfZcWzqHT\nL2HzKuHU6pzoq7s9jg0R2DSoPdWVtk5ejqboxZoVvXQtDQ9aetEruNSGpUUNUaKQQxipkPmFNbWf\ngjFADV6SL6JjECUqZTLYTfxdIckf2eUmuBQiN7fdgkjdQ3tHjnqLsKZVwt/ntVLU4wL1KFZRlYqA\nMlUT7Sj33iNKOOYM3QM+emwNVLfo1gi3GZjjUPZiu0VrUp7Vo97LqNldZRymCuHYZpbP93vLGKvR\n4pJ5MtiOcn0kN/VIt0TPZA2tu8X4Jlxu8oCsfRKFXUKHwz0SbGRpZXUeM9hJoavg8DahyW3JJkzL\ntFgLJ/dhFlHA25vU/M1qT1fakqc/RLZMuFCqEUFxM0fQUjLiVRUsYT3KOfibvfB8id/ZW+b66mWT\n0Ne4LwZbEJ0cIeoe2WOkdALqnCM0ufMwgYvg2kxPdzD4CQO+9MkE6uPk5eE5WjfNWA3BMCHYG3IV\n4n2MtPVvXUFqkBD+pHCfrOe6VwqqjPTjQoxrfW+R52l56gheLvK5b+nkmNn6Pt/bPoHcBVpyd24T\nxdLXQ6hPsQvZcrSKVo4NSCyRNArTpLMd2hC/fxmZ27TKO6lBxGdEk/SrvTCILjg6EVy4l26iz85A\nq55QBFp5EABwcUmNrIXPO17vh+bERUHJn3+Otp8XTXDcpQxSDnrhOMb3/et1rnV/6jRSkzyr+aQX\nf7nMc++2RIGMCGCVESEpYgX5Et04XxoqInmcAZ7+uh5vhlkpTzcrun49+jM0T1HWdu4WEZxj0OEf\nV07g3WvsuOSb4/rVvEBcRBwHCm1on6WMuRHPIzFy6HM0fTbcu2mo9ZQlhg0LlA7ONyUXDU5SbeyI\nvs4GRwVVJ3k7uFaEXuT8bkopu2zaNkpVWqBR2JFv80zm3JtQFYkCWNvkkWashZyJ/N2WqbDeoMy0\nZUvYzXKt1wYpfwu1NszrRF58OjXqfnF2MgpI5Ian0tZtfCEuXu8EGfpKsAa9hZCy3vsRLucoHF2x\nMWQi3BSZYOjB2xUoTRSa/lwRDQcjfyVnvox2m4IpqObltuu7iXERGu+6rcDNQxSIs6YEQn4KLus1\n0b5rwI13MzyM0jt6KHmPYbnfA0WUF9yLxyl0Fm5YIHcwcjCu7lIHDcD6m9xI3VgQ7RVeeo2sFHkP\nGbUTew7HdCKKsMYLae3GKI484UHo/+c9iH1CKGq/8kPYRYeffR1908XYDYzNUoCtRkKwdEhbOBNH\nXEPhKrfyu5N7WsheFMUFFuuQGEU7rGQHh0WxgZ0NMuRey4SW8JOmVn/elTZlrQNphodboRANuiUl\nmEo8APWKBhmRpG9oVYAW4Tx5lJC602CBqsUDYrCqUFWTTonchbqOrKmSCfg0oUeuLRO/ayNX56Gw\nmpxISrkfWVHbV1rNoFPl4S9KMlAKH7CuVEenQTprRgotpWhJ+YsjU6uiHqCQ8qYotPd6YkgqRNzA\nAw3WR/j3MfksdFnRSjJDX+yeywvzK1QUmrftgI1Rs6mkAs+IdKGFMAXJ9LEeGN/jOoXdERis5JmI\n5ggKC/xO4HgQAFBNnsaOldH8fWErCqJOsnapg7SOc5jUUfEJBrrXj41tmPDqSVGYYFsoBNkHSKUo\nzJQ6N756ijDbQqaIRIKKh0VDATfmlEGZ5DsSmIZDwvlg/AT0NxmV3DzOZ50cV8GaEeU7d9O4P0ue\nGzJocU1LpbWd4r5bZVEoJOSjrO0Uxpq8/B8rXDDVefHqRe1u37C6W40JLI6rkXvAyN6BC6LkZzSI\n+bao7bvqxlZPAAAg212CLcUzkjHzXAxWzXAsMNr350MDeKVOof3uq3ZM3iUMuaIU7RwHLiOe/6wj\nziyaRtHWsiiH6zCVidQHhJRzjg08clKGze1Z0B8g/+bNQ+iMko9+sPkAw7tLnydKjPalPDbucD6n\n97MojNNVFGlwTSc3NxFcEuVYZ+exKOH/v2YrYiPJddVZ3wAAuI57kUz8OwDAj6xO/NpjdmFatd1H\nykZZacuSTq/tKJJr3M/K1Hn80ToVzv+7JkWf/acAgPfjlF2/EelFv4vdn976ZAv2aboRlKZRjIWf\n0jsVAJy9iJUIcVe8QchE+z3tLpUno6uOkOgGpm+ZUBdlctW1DqR6Xow6Ud89ZShDE6WsqGVNkNuo\n2BRkgExkPqRllFsaewfhJNe/ihL0NrrGSlUHzKLAUCXPzyaaUUScvC/SPTW49khzM1EAtN1djU8b\nB1DzwTgYB+NgHIyD8UscXwiLd7lJzfyoMYN0ryhIf78HuxpafS21A85nqG3fuk1NKK+7BeUJamGy\nYAzGDWp6Pyr/DL2iboDdTa3n0INxOHOEkndeDgMr1DYtn66j7KLarHQzcGqlWcOslZbyk0QODgut\n5z6TBM1Fmr/LonOLBRno2rQ4YkKD+sXhmaEmVPthAs5JalCJhBFzfs5t1zGPZk4Ug3hAy7TpyeKt\n83zexe9mcVchiiiYX8RKlTDYIBFIVKfU2HxMi0xxRo4ndwkXnp3rgecBra9FK6NclYaPkXhCDX84\nXoDSTRg8mdnFkwUGEIRFpPhhWxoaERSTi410pU2hlEIhIB2DKPxvrKsRVDIAZtjgRzXNdZd7m2iq\nCLH6ytwgSzOPnGja0NIDzixpltsaqOb5bpVaNJ5Oa9Hu0LIN6ZWwi9KXKUMF6qiIfpVRoy7J0lAJ\nC6fVkaEt+nTWGkkUlNxba5Nzybq6R5GG1v1waGi9GbTks8XdffQaqPHKA4twiz3M5jLIPBBR1ucZ\n6DKk1aOSIj09thZiJmrrjjkpkhUiJ4MuUbRlfQalcfK6XdXCXpJWkrbZwLCLUfW3tqldD5WuQyFy\ntXX6i7AO81nyegpbe+cAAHkp0Z/sfHdrvr+vDxBFKxbHaLkOJDR4cY+8mpvag6JJFEqircAbJX9F\n+kUBlJIKq2kG44RGV9Az8FUAQPl2EqVnxPkE6R0z38HaOmFhdZ8Bp0K0osq38pj7SgAA4LzH/alj\nHeE5FnqwrKVQiRDB2LFs4aUYG3bcU3Au7sZAV9q0yyHU+8nXS+uMfM1uadA3yfUzzZgxJiKvd8oD\nmBa0fV9CGoz+CDKit+zRLRneMBJx+N2VQdxwkpf7HgvXxlgM2xnSoHdchaxAmNcV0KKgJh3VYaJn\n545v4fo+ra2M+hi2tESRhssdjDwi2nFW68eArXufYQDQ3ZqAtEqk5tZiDZFlPq99ibwzf8yIF97j\n2budMOP4aULqAyunYTtGa/DKPa6jbbuMwS3Crv9UpcV7MkYEH4quQvdZmUY53Wdr5irO2lhYZ/Gv\nj2HREQQA7GeWkDtC18HpQdL5cCuI9m26GyYuDeKemuhBOaaGyfz06yam3oFUIGXqaBNFkVtb6JAn\nW5iAKk+hF7K0MSw6xFUVEqR1IsgpJ9yUGRcUA6TBmqminOLd0DS24LCTLzMKuk2SOy3U+wRqsSvB\ntpC1+s4WGn7yqrwmuqlBjkyMaNRAR4uagp+3jFJ0nN2DNJ82Dizeg3EwDsbBOBgH45c4vhAWb0tP\n7SWzGf6H8l0RpQcnM6K8X28Dj+PUZg6dpNWYXJxGMERLcenGbXyjn5qr2j2LoRo1wZiwOKLrQaQm\niPNPXlXgb0ZpxdbDEliH/wAAEC9cBgCMpB+g4HgdADBhkmImQgumvJGCUU/LvLFGn2ze3Q9zh5aD\nSQTM/OJYFGUglWd/FbphzvHI9g4+qNFqPnysBt2f0GILj4tUn+1RHF9lisb8oTb08/xc195A8FNq\n+grRfGG03UFESi1YFR2B1kitPFwroaimtVRM01LZrNoxfI5aZfFeEzkbfSrtPh1MMVEN6aQoqRaU\nIxAR/TxFD9tfHDV1BZBxTSoF0tDolNGR0PrNhpqojggfrcQJW4lrlDDxs7LGBouS66BtV+DQUg/c\nSrfQKyKxSj18llKyCq2S1tR4U4aYgpa2uVJFVUXLLvqE+27W1CCpcs7SogxNUSWonJZD4aBln5aT\nt9plc1faxswprLdoJYQ1olFDWwa3SOeqOy/BnaVfP6U0ID0tfI8ijSGqS8BaYLxC4swGVD+kRaFw\nmBBboM+03kee3m8q4Z2i5V8vTqBnlD7KyH4c7Q6RGLeU341GAb+Je7i0dxkb90in/NCrsB1ljqZr\nnlr91Xz36k759+swzDIWwJukD+3Fmh/viDWZqJWxmGUMQtzmRU00IOkH91pbUuPoNHnZV7QhH+R3\nfdoV7EZJW69I58rLnkFNNAeZTRdRDHAPY7EJWEUB/Wu9nEOf61lIowzGkShWcLtDv/jr6j6sTdDf\ne26Pe/Gpo3v5wcF8FckKEZU9fQAAMHmsimtp7tvJ5grkHfqvIzNpfPqXfN+XvklZkgt2sCXmbrP1\n4vlholC3SgXI1LSS7MJqWgkF0NfgHBO2X4c8xL2wST5C8AEtwTEn5/3o0WG4bbSezXMPMDxP3igO\nWXC1xHXVeAZRTnU/awAgk0gQOc11798woSbjujVynM+vBpv4CyfpcRhPYr9C6zlxPIXwPJGsE0eY\ntqZLHoamTEThf5G0cLrnjwEAseZXoC9znlk//c2n5nugE7UArJfCWErSau5BCerL3IcPMzwLE/2j\nSMb53X7nJswCHTx1NgHjivWptEWjNRjU3JdKU4raHPdL+oi/cSZ3kAH/39uSY12kyjkHO/BXiGJV\nKpRhBocVsjavtnZ/ClUD/9Y36wi1GVdgrTLQq09yB+GySL9z6jBVEoGYSyWkHVy/qUkRiLmkhNZB\nFKAtvYucirzYs19CsJl4Km3dxhfi4u3/KAgAeDyYw1GR1/mBTI7Zmqgr3JTBJuC3rXtkhhX9Egxy\nQgQnaw6s1Ej4YUUJm8Lqt66LRHqtHTmR53vP3Eagl9BMJj4ER4y/8/h4QLTTM8hWeDH7aza8p6NQ\neUGfhtfFTXukpODz6hQYFjWB93zdYT2Hk0LHsNNG7TaFb/FwHs0ahWLP35Twbj8ZxznKdRj217G/\nSIYeuLmL0BE+++ZNYGyYv/OIIgqPwwlYDjFasnklipyBF5VEK8e+6KI0Ev3sAOax3OL/n/sNYP0B\n4aGJ9Qx6xykQt0VD9s6aFOUhwktxUV/3F4dEoUM7QUYNCea2h0xQqPhZzFmFU8ScxQflKNkpYFxN\nHsZUTgKNjUpFOVdHuhgAAFhVIeT1oujCDtch3MyjJJLi8+UIfBLCS+ttQF7hpV/NcA7pYgupDmnv\nZArINLjHmkYTxRqFlFT04bWge1Tz7YkQpnZ5GdpEAE3B3IuBPJW5G+qH0OYJ2xdMBagdhKX6DlOA\na9pK6CUUoo5NPaQXKbQ/GXTgcJMCIu/hBTH9II+kKJxQiG5DYeBeGI49B/V18s+QhQrD41odsQ4F\nxZjKja2TPCP23bexvcogEys433PjbXxy/fO0nTq5joSUCtxChOtgU/hwQgjaa+tS9B8iX19S/hSf\nOJjjrUrzvcvGIJIgnHvRVYFzk+fiZtWA6V2ub2xMNBwv30TE9pnvZx7RPZZrTc5sQymh2+S1ZUby\n/kS3iaIIHlRChilxSS/f1+PCDNdnb4H8PzjaPQhpTZuCf56KwshJnvO26hAO5fn7inQEtgw/n11T\nIDLDDjxjIkDvlr+IwD5h4rJbCbX8KwCA/XYVkiU+Q3+UfDz68XlcFu4wd2UXuQB5+XD5BEpZ7vet\nAGHpvnod1R3O3daexe4AlU9XW4aTI/xclXuCnLXQlS4AaGe/j4r3G1wT3IUsSv6UrPO9n5724/Rb\nnPvuxC4sDa6DZcUAmYNFLQx3CbP7fM8gOUxBecLdQKlJqL35r7W4/T5/N/UfOMeQN4l1128BAKJ7\ny2h46MLqe38Q7+V5yT7XQxlhe+8Uln+HZ0oZfxsOESB7uXIBQ5atp9ImL9pQFYpuyluCe0eUJx3g\nBXw/04RWSrnRljbhFvK2nehDS3RAsxylHFCnGqhtch18bQsKWe6tVmZAQM93rMgoV/I9x2BPUHkK\nrcwjdlQE4Vo9sIvc+fw2L/mieRj2An/X69BhI80zX3UUIK30PZW2buMAaj4YB+NgHIyDcTB+ieML\nYfF2mA0Dl9eA1Sqtk3xzDMkKIY8tSQsjFmodyWXqCmPTDlhuUJPeN6Wh7uFD1levYBiEWDd9rGw1\npLmAkOgwMeM4gRtaAX+cPIt7AWrdIz95AQCwopDDl6cGuXq8F6ZlWqll2ySWN0UlLDMtxXS1gk1V\nAAAQSnWnrbhFq+eU0wGJjTDQo6YBgy1a1YvaBpwTtFBU1xiwAvVDPDLQCh75ugGP12h9nBurY75G\nmPuRsFS2rFL8SpOa+Lr+OOx+BlcZ+rSwiQLj2R4GBJwu9qKV5jpW/9qFr87xGR/NLkO1Iqrx2KgF\njzybQPyjo+L3m11ps3WMiCu5B60YF2CjlYMsTquwXVFCqaKGaVkGElZ+V2UmvCsxNbFcIjxsMxtR\n74jyjXIDlCvUQgtezr1W0kAq0nqkWiXSdWq80lwKpYZIU2ry+Vs762iJNKRSI439Gi01u7IBRYvP\ndfk5r2azO1JhWnEjLBpnWHa4NiprA480Is0pacOOhGv5rP4cYjqR1rPJ9zo0RjistBwemV3w58iT\nr2aX0bKIfO4YNfH2BT3GjNS0FxRldGTkmczWHrwz1PjviL7BHe06/EGekY3aCYyKXOB53ygMec43\n6KK2X1QHu9K25umHbIW8ceY4LZW13SokooGGdnYXzSD5/qcXX8SMhmjQmiinN7HthH6H9C5Mt9HI\nkH/7PCk0ROU0tXBjdNpudLbI65GHw5DZOHdp3If5CoP+Euc477Fba4j4aOVe308AKQYrPXNWg8s1\nWoI+C3m26uieN5m3HoH3CIPiFoMCpvzGCqx1WodvXlHjhaPcz8ihB0gJ5CPfIN87nCmohohkDGQ+\nxr1FPuNSRALNYeas7q9yfxT2dzAnY8qOylBAOkG58o6xg1knadNEiUjsamPQH6K1FI0FgDDXJ9/v\nx2iJtK03GshUupfCBIC5Y8/gTRGseKxZQlWgTVUXIdjAp+/jb4u/ynWq/xyhjd8FAMye+Df42iD3\n+Wc7ovpTdhGt0F8DABLur+GMKJ1a/RcvYeoNBuf9ByNh1UBkEaoJWvC+ZRcyb/I89Q0HceTqb5D+\nUaaU/bvaVfxX2+TVZOsMmqIDkmH1jzH2wb94Km0qeQd5DXldJykhIxCtaoOIgTuvhFFLPovpe2EP\n89zqHBrI4/zbIhAFWcMJ70UiL5GVMtwWkVqk3kKizv0oN0VJyloGDSV5QDl1CP48g9NyHinkBj43\nmSGSZJftQ6rmfIo7akidfEZe+wlM8f+8ylVfiIu3/QwhgiO7HiwpyNzPZGLw7YmyiZk8dvK89PJ1\nXkKtoBRbvWS48cNyZEMChjAdQ0UItkE9fbX3PR5o9/n/Ul8DvSnCgYnEfZws88KuH+XhdxssuPmp\n6NSxY4ZphsydTCQw7SDsFHayDJqqNY2SiRfHKWd3iGhIT6EVKVTQ7ufh79ds4NNtHv7ZoT30Fcgk\nT44FAQAd5RR+e4NrslJawVkPo4pzt7xQ9nNux28wUm9ieheZG6R3cvhD/PQSmW8q7PyHGsuDu1Rg\ndtoVGKW8yEZPX0BI+DOejxtw9wz/7hURx/XgcSRmGXnZe7t7541Usw57kYIi4uJe1XfyqFtEdGIy\niiUtf2s27kNR5Ds6otqfudNBqk24praZgyRABldnyygbRJ7jAwr4VlGPmlowt7yMtlwu5pmBQsU5\nx+LkDUmpAZmXB6yyVocE3JuKuQ5zhnsgE5HO6DN2pc1XiQIhRlE2RZvDRNWEfgHjKgJa1OWiPKe0\nAHMrAADIKLlvmsI+6hJegBfm+rAVIxy7WY1jXOT8xXoJp6nnlVgxUbBNDkqxXyQMXJesQy7am00s\nCJ+0YRAyBSOOFzRmKERJQuO9DOwmrkkpRUUp43N1pQ3vBLB1nH5ke5glCl01LyTCP+1L+RHr4Xys\n721iZ5B+5nGiirj+1Q5U+7zc/A/LWJJT6erb/BpqTSqt61kqHXlHBjJRz3jNqYK9zgsztPFd5P3k\njeqtIABApdPDsUU++tKwBqm/5xx/7t7CUJg+uce9ogPQle4+3q8pK9jVnwUAuEWhFtWHd7HdI/yD\nr0hwW2Q1PFM8jHiLvLp9iGfw1E8deEsUapE7h/BrVZ6dR+NjSLuoUFpFSsFe6hhGhFvg8a0n6Bvn\nxaJrP0Ss/D9zXcOEsg8N7SKaF7Ejeil2RLTSqMmkAAAgAElEQVSzJZUFQnxGxzeM8aHPBPhffY62\nmzUdJj8U3ZnGDiF3nHxiibOgRTllRu8L3HtVfQsvJXmxyt5R4/86zUui18+zsumchu/BBQBA+P5Z\nXN34UwCAzVHDwJfpJjiRZvnJ6x87UerjOXRsLsJylHP83/RNRIL0Hb/wQ/LaNyQq+Od4OX13/X3M\nxcmTPY7/Hne/QsMDf/c50tBpKaE1kzek7TRkSV6WXj/XZrMih0R0ttLWMzAoBSwdLMAnSqQ2JHyv\nUWZBWsL7ogMF9kWNePWeBk4/3VXeDC/bUjmCkpLvkisrSJT5t1QfQzlLl5BZdO0yOnphTZHXawNt\n1EX3IkVCBpeie1vYp40DqPlgHIyDcTAOxsH4JY4vhMXb/JQNDNYiUaw+z/KRvgUzsuPURlvjFgx9\nQk1kW+Rn9sqe4DRoxWbLJyBJUR33GftRHBX9YNdoHU6oU+iJ0jLb3KtCoqJG6x/sYCnLKOnBIqG1\ndFQGkwh2OtT/CK0danTOmAdOFyOY405qhCOTKkhEAX3l49MAvvM52nJ3aeWNfS2A1V1q2uHAJP6x\nmzDGUuWrkDT+CgBwsSWisNt2bBq5Ndn0JgpNWmzNX9di/OoFfmc6CABQrMyidpIanacgwSsf0ToZ\nHbyFzW12JJFmCU+XvK9hSOhahWUrzKJrT2NWis4+LcSRMv//75QWjInIwdVW9zzePusQ1lq0fPIl\n7g8qalQToleuRAGJyHvrNHwoa6mxVkT1mHYni6qae9EwelBf5n7tIwJVjHuvrBLqq1hKaGREX918\nG1oT59solBBvcr8rNVpbMlkOeeGSkDXKyCqp7edqSliG+D6DgZ+pDd1LDyZ8I5iq0SLNmEW/3yAg\nGSf8GSvdgVRO6+tiKoTIBfJBKcd5N/t60bIFBL1FpFW0Jk+pPJDtEBqPFWkVxjdlmBDviIWSaKu5\nTprnOsj+Pa22+gVq15GHbbiLtJ5fsfUiWaU13tevQ3WJVuCKlusvv969SQKOL2K6KBqfq0RUdMKC\nLQfXV7nbgtLAuRkCISyIgLRDxiAAIH/zOM45yNd1ZQlNURb18vo+ps8I66BBpEdZKSGWoLWaUC4i\nYBGBMFYPDu1w7cNWWjrVlRzURaIem08W0bYR6jzfauN74vOXJghpvpWbBK59nrQbhRp29pib35Ni\n3r3JroJVlNFMrGnw6rEAAKA1VcPiqnAfPWKzlJD/DF6zUCY0atPYfZZ0IrwKq4Tn3rBHHvB4NrEC\nrrH3xa9jc54WumO3htEeBoMWekS/5MIQOkF+99G5IgoVcV4cHmTttKqTq3YMmbuU4xKjUI5iZowW\nbXB/CHPC7bTeyz0sjA7h7Ec8b0sjXvzpMb5bXW7izDLl42yMwVnf7VmFRJRr7Y2GoTZxL3Ij07j1\nbULNxW9RJl4wLWL+zxg89JH7Ev7x6N8CAJ6Pe+C6xHPWeJsQ+NYU4Gpw/cZGZnDvFtfsW5UU/s8X\nwk+lLTUOuJbI92lPB2oZUYXtEvfH69MCIhOkYPdhX87vWlw9UOn5t6LEuUQVMeg3aIFrtVLoFfxd\nvtLCSpX3gFqUsnVZjajVKXcNDhPsUaJYWs8egtsiMM5J+fL4ThNqr3DHZGvQC69AWmNFQ0HZfuGp\nFP6n4wtx8ZYmyHh9ZhmCaxRm1dHHcKYoHB/c6oVbxYPzh2LG9289C9mrPCy6n2VRMTEK9q7+bZxL\n8+JMDYr0iJAD7/Zx8c57XdhfZyTi6uYMvIcEnNgWcO6Tq1DqCA8txhYw6qHQqb8uxQ8/5gYFRP3V\nB59u4rQoYXkb3YWc6RAvjp1SHjkBn/6uaw63RPm95sYa0m3Ot2nmpZDvpKFSEBp7bvI1fJQkfNmT\n6KD0dQFvJAkztVNaOAtk+v1cP4wdHrZC/DSe+RLXNXKFhRX68g9Rt4qLzJHDiy5egNfjLbzq5vti\nXtHu7U4Ye4/pc1arundMUbg70AlfCVKkP1fPQ1HkJoWtFejTfF67HkXNR0jIKeF8HxZb0Ah/b7uU\nRqHA9XGZrJCquT7GNulJRmWwiebnnZAUWcEH6VQdChE9nBcdR7ISKdQiK6OoV0ER48H0jBnRED40\neYD0GrTdQZ+YbReVdSomnjIjaH0BD1ylIADAYh5BXsm/5ee8GKryopL289+SvgmvhVAdnKcR+HtO\n+IE2hD4nLxqDhYdY/0wb8TL3xVWR4PEZ8mTyT/SwXyJ/2UJU+mTJEcR76AJYjjSR0VCYKVstNKwU\nMCOPOO/sVBboEtU8Yi4iIopILCrI64gm0C6QH1LT9zD5hHz/0K/DtJTpNZf3yf+pL6/jipn7Llvb\ng+evudjzow5860+5h3/+FSrTE3kldF/hcz/9nheNIgWpbcaHHTuhx40V0V3G30Z0iPzgXj+GlIn7\ntt2ooscuuj9V+Nyz4/NY/DxpGNErYQfPU/8A9/rOzuuoOphGM3YiA2QJ9Vu1CfQaRVvKOt1IF8of\n4FqDqUDLxgy+8oC07SZ9yEyJ8qh+Rvu7rCp0RA3kk3daqF/k5XZk1II7QVFffZzKwzGZA5Ey6a1t\njyDppHKUCxowfp6XWj0uR3W+ewoYAFSMfXgi5b6M+hbxppzR4LF9ust+68kVFE7S5yx11nDqMc/Q\niv4+9JM8G+Eg5Ue/o4aNJC/Fl8x30WpcAAC8c+M7CPwfnMPJ/+EyAOA9w0UcHaBsen31EbI/Z5S7\nS7WN8lnCsW+JtT7dm8J8hmd24LUCjDd4zspHF/DVbfqDf4Iff44244YOtRoVb7VdDV9B+KKFcQCN\nHZ0SlQ6HJwtdkJeiAnoYbTxzGWG4eBsNRCWMB+lt2RDZ4nNNGifkWeE63OEZK7sHoBXxILn9DVQd\n5GtFzAq1cJtIRQGOgZk2ijUqpxK1FR6RtjqY7CAmCvr8/x0HUPPBOBgH42AcjIPxSxxfCIu3IqJ2\nO2Md/OYSc8Tevv9lXL3IYtv1zRvQiTJ5j4oMSsqbt9G4Qy2u/XoSmnu0Qietz6K4RE0E29Q2o4F1\nzAqLZFFmRFH04JyataB1k5qPwi9K9hnMGKnys8XTdXj+gs+KB+ro0VBPGZUS6vM3h3DTy7kPKjtd\naStkqLmF6ot4ZZSRjh9mE1Cs81lOqwsNUcSgbKXmuyVNYFD07n1Qu4ejOn6+NuqG9BrfM9IvonHV\nEuhFgMjykBH2nxNi2ZGF0RaWRFQ0Kh8L1GFt0NqKaKbxrpPa25pxHXUJtdSdu4SXapEnwCB/X1v4\nbwB8+3O0eUwtNFY5zz1hzUtH9UhvUKuWZ1QoekX/yoIEtRy1/GqbFoemYMZum9qo3alARyeaNhT2\nUBO9OXMQATJaH/ZDfC4aBTRywpKuxFAVObupokasiRrZCq0ltaKKoptWlBkyyJoMalFLCffqpN37\nuk7uNOAU+af7Vgbr9K7XUHmRdEZbHYz2cA91hRwebpCmZ5sC+UgMoXWakcyaHRNqGUZT2+sDiAsI\nUJOgNZAzbqESo+VU95RhU7CZxuy5RUSfsOxh+xQRjlIjjIifVp+hsATrKuHwJ9N3YYiRF/MCJZCr\nuvdR/ovN05jq0BQeEk1A0i0DVHrSIN8x466d5+3Mghf7PTxbzjFGJz//4z0svkw+qljV8IqmM2HT\nz/HBYdKR2CHvrOqtcC3SopjWamAUnasq5SfwOsk7wXHyt1O2COUVupqKARsMmzx7m6pfxZGiKAKz\nQDs3Pd7dwtizb0F2iBabTs3vTBgeYVc040g0ByFSjXExPQWbl3u4X+T5v29SY6tBy/RMzxQehmjt\nf3nSDdVNIjU5CfkieMYArzC73zDn8C/3aD3fXHWifJTypi46fG0pOmgnhEukGYdDRyu1qPsA6RCt\nN69Uilj/YUHJ9z5Hm6aWgb+feytLn8Bv/jnLMX77N4jWrYxK8CsikyOx+wxSIQYSTr/qxk6ZELYk\nQHh6Ta7CN12isL/06zCl/ncAwO9HGij8W56N1OvMud6L1HHqCt1d5pEWpraYExzyZPHkB4yWHp4m\nb7TPh6D8iOhj5eMO/HXyfXF5AJ2vdG+2AgAxzRamFTynyYwNGbnohRvnXNryHXR8XFPFvAHOftGR\nKKmBRASPDtgoB0KSCQx/ViRFZYGyLRoieOKIJMjXPYL39g0RDOZEr+KOE8U2ZYxSoYDOzP3Mtfmb\nfKMJc5rnTWZeR7TOc3HVWYKr8fTCJ93GgcV7MA7GwTgYB+Ng/BLHF8Li/bKB2sv37voAUWUkZ3of\ns2tUTa8pliHrpw+ms0NN2+cvIGylFWD4aB5rok2ccyQLzQAt0gEj/Q+f7khx0UerMLG4jLXn+VxT\nsgrJjGjl1Uetxxc2I5wTIedb04i46SuQ39Eiq+Tvbm8zuKJS0WHsMt9RG7nTlTbzMP2zwZXnMX+d\nGrx7sAqlkb6EVGYcfQPUyNYrwpp1HkNSVGOyusbxcIla48hIBM4Zapj5K6Is3uHrCJboi3Uu56C4\nSIu3J3gECUWQ69AUvS2rWvRcpsU3dejHWN+lpnxaZUF6QqQTyWg1hotzuKb9f0jD7E5X2ooKP9Qe\nWgSaFt/rvttBxUh6SvoMOntc146iiGSZGqlIx0NKm0JL+Nt0CgdkElo1aZMamjgto5rIb61UcoCw\nYvMFBaSiNVuz0URLVMKSW6gdF9sxONzCgmy5Me6mdquz6SCxiLJmOq6jzNkdqUhCjWSCATCWIK2I\nj46dwfkqfXcvG7O4scE+s9KREAJnOIe9LK161XkZcqLtX74eRs7DIL1Asg7Jliiyvy7KZersqHXo\nD3ZqnkPip5f53Gd30V6gvzGxzWClomwQKuGLleYKiIjKWyfzXiyLUpzSXvL6wuPux/uCJItyh9ZM\nU+RGH1Pt45MI18IcMGPCy5SltcIiPE+4B2GNKEXpnsO5+/R7x9t9gJUxAOb1YXzkpvV6OkBEJlKJ\nILbB39fqbwJa8mp9UYVKnVZoTcM57KQX4BapQPVyDf1GwVORZawruIfo4dkcj+nQzX6qrElx0iOq\nur3BGJDAhRnkmkRWjjpcML9FxCvz+2rI9+nnnBJtAV3JOTjnaFXmVVpoNJz7jZIDmqOk37wtGqKk\nrWhpeDa/Xn4W3wtwD/O+Acze5drnXuTZSaks8KWDAICqvRdqPdfn+v4oLmT57lWdATsbTwmIAxCw\nlWB5wj1aN76HT16mdTam4F6G23ZkbtPy0liXofIyEG35hg9zo0QKV5cpXyfHCvhA8i4A4IhKhQcd\nygJ73y3EK/QTj2wyTelSSIvU0B8CAIqpP4a6TpkXUxyD62uc7/oiebr8P8pQF+UIZp1VvFtiowZp\nfhDlP3166zzZfgbbNpHKk1BC6xXt++Q8pxqlHKoYz55nCMhXec7c1jA8bZ51iYiRgSYByQrlg0yX\nQ84ieKecgUzEwCiE3FEb3aiOch3jKQP6RABoOWeAusO1rkFUvrPOouPhe1MrWihLXGufTgJLu3sL\nzqeNL8TF+8ErZArDm+tYOkrBeDjVh2RSQLuBaXhu8nLe6KVwaSdL6PmUzu/qbAWTKsJvpZsPkHiJ\nh6W9IcoujhtxM0r42PfCAM4uE/KpTS6hV8Zcy1aQ75JHJZizcEHvh1ZhkXwdAGDSrMF8nrBfYZ3C\n0GiJ4HE/n3tCN9uVtruLIjo38wS242QQ2cNXkDnFC7/YXsD+Pc7dNit69OpT8OW5NU5EUcvTub9z\nN4a0jd9pHyacUy/NwiTK6SkiMvSLnr7GYgc/klDYzJjIsB2lD3/vozB6eWUGnj4KsRXDbVg+5mlZ\n8pH5ZZn3MORlEMVy8IOutMkMMijsPIR1UQu3OaaHeYNCRZ4qI2ehUMnkHZC4SH8rwT22qCtI1HkA\nQvIdGAriolP1IKLi3/oUn9vwlpFPc4+MHR0acgFn6+toqrmfBlGb22wcRC3NA9IcsqDdEOGHWjfG\npVwLhehZK+10r7EtWd2D4yvEYXsENN5XziK5xb93pqWoSHn5GKNG6DKEpWRzFBi74QqeazMwKpK3\nodLDvdAWakg4ePjnxZoNYRoFERA0ZAgif4zKUT2uQnqQNA97+f/XdnM4sU/aF3cNcJ8mZDl/6wGa\nWqG0ukiTPZ/uSttSzyhezjHyNL1B/o1lewDRYeq27iqGNnjJhENRWE9wD1cSAQDA4WYW20nSa1Fv\nILlGl07p1zRwrPCiyRhFxy1DBEYl6b1tega+JoPEtEeH0RLFVxJBvmsOR7Elyo3mbFKURP1bi9WE\nyQRhyIdefua7KutKWy5dQaJBmNF5nopNKRLBEf/vcR3df4W11yhvio8LGNoRHaJE8GXBk8FGXCiq\nknmYNDyb8u0n2GtQkTKKOtd3nyThO8wLy7zzEL9Z4CX+UL2GyAnymebDSwCA1vC7SI2KvNDGFnZF\n4JO/+ggZJ/N7IbmLXmuwK10AUP2xGT97nvv1at2GdwXPZNfeBgAMJs/g8RleAGs7PnxJ9Ni+6rqP\n+oCIUB4ij6zcakG+z6JBM2dUeBRiNsTsazIMXuPl8/4aeT148ghe/CkVDP+FV/DmDC/03y9Z8V6M\nBsRLBu7rvrYfaTNl6rJsB7IR+iGOyRbQsf4WCfnBX3yONqtWCmVb1G1QFCFLi9xavVBECjLIHEK5\nbbbRqyc9hpQBKSf5y5Pi5W+CCo0Az3cTGtTbdB3sZ1UYGBDd0Jzi7FkUaIosg3F7E5GcMI46MgSb\n3EOIeDdnJIKgjIquu1ZCHDwvGmUb0mL3egBPGwdQ88E4GAfjYByMg/FLHF8Ii3f6Uzr8JUk7kmpO\nKRTcQY8ohN2clyMh/QgAoIhRmzIMnsK+SOfQRBow5Jku0Dp0GH4qXxj3EaZYlKvhHmPwBLaWMVqn\nxpr93igguvyot2gBmA8fw12+AvaUHYE5WtXXT2fQ+WtqYRdUhJW3i304kiMcVjU6utK2mqY2/6Vs\nDJEkLZlCzwqeX6AlnPqqA9UeBro0g9QOq70bqPYQzq4+yUM/Q20UtR24RNWiyS1qbG+oyigmqEmP\nxaVYF2kXCucE9I+puT4UEOSYJ4iz69T4tgNRxGrUuxS2WaSLDDIyZbh46w4HFPcZORJXdbcKezte\nhOxMZ9HtUvtrNhuQKqg1VhQDUMm4nwa7BmnRi7UtFR2SOjqYpdSkq3kjYKW1nq1E0dOgdrvvoNZt\nMKhRVtMaKmgkMIuScmqVFVZw7hkLtU6pNA7JMNe9v6KGWeREV01ydGy0hqwq7ptG1b2PpnfwGUTL\n3FNLmevwQNOCtc05thv96K1xXZVaLeIe5j6anxB98JmauONgQIoLAbhL1OYXfF44qkRivFVa6JIe\nILdDq/FD4xqcKpYxVazmMCAqq63uC6THOoKgSGkwznWwv/ETAEA64Ie1wrVK1GiZ2f3dU1Pmbofx\ntobv9n8Gp4+0kHVxfeWrF9Aj5zvcvVVUnpBvZ920dNwqLTYshDd7JDXgLFMAlRsfYqlB6yOxyLlc\n0GRQVdHKGogX0PMin/Xg3SoOORhIdLqPEO1KLQHIue9zb/dB/vtc/8i8BhsitWPZRJjYeGkSuPx5\n2nrqKUhU5PGkOQAAcCRiuGxgvrlk6RA0gh+kBhMeTzKwcXSPgXDhniWYRe54v6sXleu0olQdLUxO\n7kVOShodJhtGcpxPqKbFtsjNryz34pBAVFIWWuh7vR4Evsc1kR22QiaCzJLGV7AlYVepk+VBFGef\nFZS8+TnaPGf1UJc4n3ygjeHvkO9107Q6dyeaeGznvv5W8yHeST4PALh0fw3O7/M7dwLkz37lNahG\n/jkA4NN3N7Cip0zTX/k1/GYzyBc+RxnU/K4fjf/Ic/q9b1fxz4SL71819vAHIoDtnUHR+3yqguUK\nz8LhqfOIbzOo63bPFKLZjz5H02fDZB6GpkLLUyrpg0zHv9MCAekzplFKi+5QAwogxSCnqjcJfYQ8\nU3UJV0ApBKeJsqAZq0KV4dzaegNK+9wviZSITFUmg8kofpfoYFdK3uggBVuFVnUEpLFa7KBcE53O\nqmpoHXxHVt7Arrr8VNq6jS/ExbsS5SHXnExiJSJgIssUNvMkMmUsY9AjItoE1JxdX4OvQrO/VYih\nI+Dl/btGnBnjpj1JEJbJdKrIWcj0X1rpw88UhJoOn8sh32EU5XCTTPZItwL1IP1xz0KPmyJCd2ov\nhEKbF7m/xMtNPXQYeQPh54/jD7rSNiEuvYR5AIkwYbgZWwqJ45zD+pUy/Coe9KqJAqr4PRt6zjNJ\n/d6UHzIBaQ62/MgleXmlRH3rc4s2xMSdH+44YRf5mcbmTST6Kex/pcqLcPUDCbaKFECHPQWsjYtL\n/L4e1SYv/9v3KVRUxhJ2BgjvzUQN6NpXxGeGTESbm828TBuNOrI+CgSbtIlKmYLWWNpDzsxD7xXR\ntlVdETk511qfliEjktv1ci0SSu6XTcDE1ZQZXi8vvVKzA1ue2lFNL4UmzzXBkLjIgjYYRR50e1gN\nSZVsPtxpwOHnYulN5C2fa6gbZci7lbBcJ9W5SwEAwLPhAu4N8MBvtfKY6ZA3HlcDsId4yWpknIuy\n2IBeyn1toQG7THTMMadwdY+8atXTj99Zm4fDRmFW7aiBDcKXTWsOqyUK7kKPS9C+hKZctDYrWdCX\nFWtZzyAjytlNOSho6nfiXWlLTTnR+0AoLgFe+CHchagSiZ6BFp6Igipm4zHEk3zu7GdFZkppVI5R\neUjccEABKgoSvxX1K+QD/zj3LVSchhE8h5acDiui25JEOwtJjb97EuVvRhqvIqHkRVj8agPND3nO\n1g+p8M0Nwri+KtfGk+4esS0/7EA8wrm5hHgLNDagF7mYjnYDwcecW8cTQCtMHl/0cl6XlHY8Ea0f\nXYkNJEGFvDJ4BONm8vXddcKf46W1f2gL6O87iw+N/HtGNw9Zg/NU9FIuqMoOVE9wHQuNQbg1dBnV\nJ9bx0jq/uwwl+hIrXekCACTDKB5nk/m16/8eEhvjXv5f9t4zVpIsOxP7IiIjI733z/vyrst0d7WZ\n6ZlpzrBJDjnk0olLEqSwEIXVriCBWGEFEVpAAoiF/AricCVCS2mXInuGI46fnpnunjZV3V3evKrn\nbeZL731mZEbox3ebkKayiBUEtPpHnj+VyMoXcc+55957znePOXaM4wlsHccDPx2Q6+YQbdG2sty8\ngonn+Y6Tfuqc5/6fwujwUHzc7yG2LDoZbT3EI3GP+dx9FtuIL61i8J8zgnrB8ffwlz7e/b6a+Qz6\nosOW6JSI1F0PymLf9a//MX6383vk//wRzK3RncAAoKaWoDRpHPhsBWhxzpddXJ11h35Mivaxw7YJ\npymg5LoFFRF9fLxFgzPpnkMmxbmw1fsIgc+tah0EelxHjYG4fupaUddpUGb0ZxBRuD+0p+vobO7z\nHeLvW8ECgl2eLT2HB81d6pdFdmHJXX0qb6NoDDWPaUxjGtOYxvQJ0qfC4+0qLF83/MkGYqI6jNfq\nwuwVenprHzRhOumh7JdpsSzo95H0E5qd67eR+jY9jsDFO7iZplcSjtOLaGf+DM+nfgYAsH62g1er\noj9tvYGCkwE0axdFk+aDX8byh7ToDs/OIV/+eQBA0/0tPDsQsF+FVnlO2UU8w2f97BUb/rMRvDne\nohW2cimCtTjhsp14EHfu0apMKAnsimhdryhtJp/Mw7NLPsOBBloTtI9s8vtYttFTOVilp6irReii\nX+7mwk2cHdJTNHdUzL5IOOUbb9EiVmVg5gytzu+5rbAVROR0q42fXCTcf0k0b3i7U4TeoodqJldH\ncAY4dAdUtyjNZuNvvWEvpPQsACA7qeGUaA7Qj0/CAkKAgzqtWIe/jcAReatYFPhFpGfLPoTdRT49\nVpFvl6rBNGjlzvp9f6u5bqsFKkWBua7IA1yuQ2lTX7zOScQjtG79sThcMVHdxsLn2sW4f5rq+RLO\n+fm8uoMowttXljH/gIEaxmAZ+RV6ahHPu5hSyHO5QFhKVbvINETwy4IE30N6MvcdCVh7HwAASiq9\nbeee/LcR2dIwBfs0rw4OMznUdJGD+Fg0Neha4LZTD1eLHdQMRnKG+x0kooRLu44fAQBuOOcwqnRV\nJ/4uMqeJxFyuMShQ6TqwMUOPNtr+K0w+4vcrJ1LIz3AMt2Lkbd4A5q5xDh+dz+F4QZQ03foKXjhF\nWWfLlEdyYgt31kTk9EII0QLhOY+nhNuik9GxBPnpmCWU09TlcLaKpECLTnVL2HbSHd8WpS6V0OjA\nsQNLBFdrhCfTAaIFqZobWoDv+mDFATXLsb/g9uO2yFqYr1L+Hw1DiDWoXINng+h16Jm2WxJaec73\nbICeV2rSxI0dwrnXvLt48a5omL4UQuGIz3XcDorfPkD8EveKaD2CO/e59mbXEtiNc00GbjXRvjy6\n9zUAlKIX8PwWYflh5XN454uU+6/fpWf7F+5FeFaoA6c/XMYzl4nm4a9SSB0y2twqcv63z/+PyO5w\njZz4rB8LdSIfhSsSvukkmuB/gxWmShcv4NKNXwUAhJ4pILb7JQCA53gZNXFlsTTgeyNnr2OpwHV+\nrXwfy2nyb7l9gOU3n96ztpOS0fVwT+yox5E7IAIRC3Es0+U+yqJkaUQOo65T73teDZNVylIZkh9N\nPYBiIZ89px2HPe5/oVoCq1YGlxoeetRz5Q76OnXd0HzoVYl2OHZt6IibmuCQe0SheRyDJtehaXWh\n7eT1pVQykUs/lbWR9Kk4eCNtUWJMGsJ1hgvg1usPYLzFDejsShUZHxfsokiqb/pOYvkOocBbJ2Yx\nJ+4CX6j1UJa4Ub4zFGkXrdeQ+AIP1tu30/D0eNfgW/bjWQ+hku+GuZh+x3wPATfvVDf1O5g4JiLt\nbiRRCAr4YoIHvlaSEXZT+a/lH4zkLX+aClD3e+Hb4aLq2HVc0DmrfVcbn93kxH4zSOjHLDmQtFBJ\nj9I12B99HwCwp0SRsDLU/4GXiun0ewFNFA85UGC18fs7jTSSQ25Oi+IOaCe5ie0iYc7h/TSqO3zH\njYW3MfhjblKry1zYuWodL1kZ0bknIjca57oAACAASURBVAF/mqxOE5LocDQ7y43tYTuGhFMcdN0G\nGhZCzUpcQkA0I98VkfdSIYLoJBVdK3vQW+R/+Bp9uAQsPRR1mKd909CsVFeP1QpF5WeXR4K1JOov\nLxIuc5oa/AJ9Rr8PzyxhaZsahzXI59l1ysxhjo5GnNE+xF2XqC5B0eBiv4ijY9TJmcoezIIwTA5f\nQNrNQ0I5Rpjz7eZxXNynblX0+7A2+ax08CG6Lm4m/Tw36lBiAJuHf1eSarCLlnsVhwtnFOpXpkuj\npJp1o+4QqVaTXkwIA6N6uoCMqNOrdnkYuIL3RvI2UQIicR5glXdYpCY7E8XJR98EAFyPfh7PBkQR\nGVsUtQw3xH6Y7zpoZeCMU3diu7PAhDBGkrfRucANrfU9GpnRC0X8R49ozNmDYWyJO7QDrxXnRHR2\nkbYZMs+14SxTZtfywPGLFPzJ+i/g2nEmD53b4nqq2Ua3qrQ92sHmpEiNGVCfio0luMvkx/n2AOoZ\nGj5v5PeQPka5dr/HNbKlFVBcEJkVWxWY4jVdRxr5S9wj5DxlpsvP4tRFXt3cvPYKjCYdhQe+bQR1\nGo7rMeqZ23cRe+ui/adsxeVl7nnJ9924d8C5/yW3ij1bfCRfAPC9/X+DM195jWNotPHlHRqGdy4x\nKtrT34b3z7kON08sYPbPeBh+J1pFOMYF8Y+zPPz/oKfhVTsjrn/Svgbt42Ilt6J44QQdj5WrjARv\npctwi2jqcK6FipvzcvmjPMot7keZk5TN2/eWEP0V8hlK/xHsz1EP3Ne28YPf59yOKmPadHYwcNLw\ns3XakHziOqAv1pDhhClg3s3qESS7qLVcssJu4d6faVE3Wg4HUgJqjhlpWKzUyT5qsE5w7WmidGYV\nYQxlvqvTz8AusiwaoTJKReLnziH1u2yVEevzOyN/hEGZe6mmpjEMGU8y9XfQGGoe05jGNKYxjekT\npE+Fxzt1jNbUUT+Ewpu0BZaPW9ERQTP343aook6/eZxRfcu7FWys0Hqz3nNg8AVaejsbGrwJWknz\nFVqx1rMGtgo0XS/kVegrtJymsgrefkTr+PJpel6r/TAcm7SIly6exn6XsJT0M25YN2hhpkQuZ6i9\ng+s/S3j4xO3RebyySgjn6PUMNv6A8NMv7F7E+x3yPD0P/IMFWl+/lKcXkd98H7FfpJex/JMlBM7R\n0/jIBL6e/QEA4Pgc8dXDZBHJtvCeU4dQf40BU0qyhcERrfGOyMtbSSSwKzyG3Z93YnnI6MP3H0rw\nnqVHlhNQ9kohi5sHjFge9HwjeTMUK5aFCu3Zyc/JwTwyp2iNujIq/CFa0q1OCw5RgEQT5dWkiAe2\nFOcwtKDBYhVRzUEXLB3RxSZGj29Yl6AGOccDU4U8FIENTgNOryhtaXLeFyQ/dI/IFR5EYPGKogLT\n05BEkXTDT5l2m6Ojmi2LP4dTdVrCD4XLq6UkaB83g7hs4MG+6Il8aR3SdVq/3iChd6OQgmoTUdb1\nCfyLBcrw1+9a8Eac6MulFj3097o3cF4gNvKb95EN0GMNtdaxWxLlVGOMAHZONoENelZnpS7eD/K9\nU3/VgkdAwptlFtswj6cxqsrE7X0f7C3qTEx4h/2hgkyb3kt34yFuufj5Em5jbUjv7PS7vLq4O/c5\nREUBmKy6isgRg3wGJ76La3fodf/BHOfiT96zYfvVfQDAb+zryIQ5tqX9C3jbwQYNp06xkIPlgyYu\nTHB9t5ZmYXzIdxRcb6JZZAekwJe5htwfxZ5kDMCyNo+oxDGsG6IxyrSJB+cos8pbX8AwwJKcQWcW\nQRElbC7wufFgCitZXkuVVlvQfpt8zH3HinqWuhPw/PsAgKPqj6DkKBMdKaw5ebW1UnDi0YAoy4kK\n4d5BQ0XHTiQt0/g+4i/zvQfONxD1UQ8acxcRfO/pHXw+O1xC62tc/7cnDDzI03t7cUdE3+4W8dtX\nGW3+5+YUPvhD8vTsX1fQGHJ93z7D7/6TB1Z8N8ArCUsgAuMf7AMAfv/1Pu5uE+HKZJkfHP/CABtb\nosOZ8/fw3AL1952Hb+Pyr3Hsk/tE5XrSb2PtGhvuXsUW2lXuj4NQGC+tcf1/dQRvM5KOgogMlvo+\naIci/3+SXnun/xiGQ1ztNBcxcBJJqFQ2cVuUf20FRC2GugXhHGUznLFht0sP3OXuwy66VClO7p+m\nPwdniftjIepHNyX2h24fmzGO4flD8jArD6EHWRqzUwqi5uUe3dwcYurk6C5nT6OxxzumMY1pTGMa\n0ydInwqPt1GjZ1ArtmBMi/zNdQnzwtOY9r4GeeZ1AEBF9OA9Oj0Du5Wh/lc8fWwlaU3Gpu7howEt\n6XiCQUH1pgJnmJh/zfZlRMO03rYtVfQUWjhnRR/VD1c86Nh/HQCQ2fkxLk3Sottcq+O0yMnrz/Be\nKOBqQnHS47gU9I/kzSLTKpoP3sf292hp76gfwg9aSJH7Co51aYXdEekKkYgHP/6A99dXzzXw4bcY\noPDW4DaW1kT+3+/xO49yH8N7vEObPS2j8t/Ro3j7hS7wBi3+jSa9WFO7huk+ZSP96RHWRaUnbW4T\niRKt5mwgKX7rhK0ucgQuAbj+JG+K5oDVx2fEQrT27UM//HVaoMOZKvINenpBSwSFIuU3JwIbLKih\nJCqHOee60FR6psWUhomYyB0WKICxVIeUoldY9XeguvhcTR7A9oh8Dt18lrJcRDsogqhSLsgW3j+p\nKGAg+t6G7ZRfwTJ8kjEAmdU9SEPetwWO0RI/qHlhbfBzvJ9AfSj6h+72ED2grNoqkZOJxgWUI7z3\nP+wOsezl3O65VWR79GreEj0dlh9JkOv0rGq2CIIm7WGrHdgQqTbBWVYPy73jgM3HMafzefRClMnW\nCQO1IIOUZotMRVOEx/7TlG8m8LzIyU1LDPDqhfJYL4vynv2LsG/x/vowlgcKRHNu2ullLtsyKDvo\nVU7v11Af8I5ySp2EKRCTH71Cj2PhO0HkClwb1w6P4K+IgDKjicANerq5FL0aw13DnSy9Ke/cNiJV\n4VktfhGfPUa9vvl9Iish9+h5q5SaaFa4rS0c47833X0E64xXcEx8H3KPMRoHbRNfKuwDAP7C9zzf\n27QgfkB07Fs/vwfL96mrv7Z0D3dFKdnoHO/8fP1J3HXw751+HWGhnweVNp4xWGZ0d5EV4aajPQy3\n/wQAEOifw9e/JtJwrHEsiSpM9z6oQ3p2fyRfALCbyOL5pd8CAGjpr2JP9FN454h8Rts1/BcBzot7\n7yF6omlGLRzE3av0EFWTa+XmBzUUp0W++Acv4/fbXA+PbS/h7Jn/BQDQusJ9+cZXq3gQ/McAgD+S\nfoL/w0mP+Oc8HhgiHWvjm6IC2mcfohYiSnXP/TxS/8M/J/8v/DI07ekRSIctOyat1Llu5gieCNf/\nsCjmWZbRTXEd50+04E4yWDEVOAm7aDVpS3J/qXoSkAwRWNeQYO2IZxzmkBf7iiHKQZb2JMwpnNfB\nFhBQ+XclhwfH9rh3Z+2cK0exiF6ennJ32Ic+xeeeDMdx2Gw8lbdRJJnm6Fq1nyRJkvT//yDGNKYx\njWlMY/r/QKZp/lsVbR5DzWMa05jGNKYxfYI0PnjHNKYxjWlMY/oEaXzwjmlMYxrTmMb0CdL44B3T\nmMY0pjGN6ROkT0VU83/zl2w0YF+pAwfMGZSmDHgfMDJSbTawZxPVfhLMozz17RUcuhkNfOL5PnIf\nMaJw82UL/DZG6LkeiYYCgQWYM4xkLr1TwVKYkX1zFhltEZWYe8gqLn71AXYd7EPrjPwQrRDzByv7\nOZyZZWS0VmNUc7ZhoLHMqObKdR/++D/9whO8/fN/weLi5noXELmu3bk5eGyMal5XPoRvk+/QHMzn\ndTceQBcFlUpFP0JLnKbGDQV2p+hPe5p/Y78WRTPEKMySvo++g1GGfYuCZZHrlpUZCe0uDZCfYVSf\nK+SB/RFzbKdVFWWZMmk7KcdaNYvTBdGofcqO3/2nv/YEb//wv04i42OEbuI2yyOaiTw8CmVSCFjh\nE3mvva4NZovRgXUfxxXKAtU4eVOlHoodUWnMaiDcFsX/RaSzjhjiDsp9d6cFLcGIwogioeZjPEP1\niPPtc/vREb1c3ZIVXSejYzVLF3MHjOPbv0w5zJeG+Cf/wYUnePvaG21AYseWu21GS/uW34HjW2ym\n0YgWsKWT5+Xz34Wy+lkAQNrOeX3W24Oxw3lJWmq4KzFf9nwtjUKafDz/HKt6Hd20YeMyvwvmHqBy\nehYAcOXxDt4Vueqer5IH9x/uQKszgrKlD7Fk4XPvGadw3MGc0ftbjHK/uHQfv/3ia0/w9o0/XURe\nRKNrotqP65qB0kl+ViJdOEV3F+3GAN5TjO58/JiV1+ZeamKYYpk+PXscA8s+AMAwDdhl5j5aYswn\nrySdCDmYfZCR/cgdUWZRXYJ0gVXWijcYzdoYKriSoG7kEEMsyKpH+b0EOgZ/G5AZ5b6eK+Gf/dnD\nJ3j7R78UR9DB39ps1MNSuw+Lh/JragocIoNBs1kx7FHnDD/nLdxOw1elTh7OGGglRRlC1KHLjMh2\nKNyjdJcBm0w9HfTaaNa5XlxSHUaEkbb2DtdeBSbsEiPbywMfLC2xJiM6aiL62GfTkRMV1/7kL5/s\ndvPf/58fILtHPXHLO9B0RlxXtkRvaR9QtIomHcEmlDbHYwvoyNcp15ltrsdsvIl50bWnPT8A6qLm\nwcEQvSDfHRWR+KmyjPY09SFmT8GS4nsHAQ+sB6Jal5sZAIlwDqfqlOXN1gBtJ8dz3O9FRqdc/8v/\n8Emd/LNv3UG0xL1rYNXQrHKvkPKihPDyAHuq4C2bhtfKfPlSpYKBX2SUdOlHSvY+LFbqZ0gDLEXy\nYbg17ASZfRDqU+YOvQBbk3JqeHU0d0ROcEjF1JBZAYaF681tmUJK9Ct3FIcwTNGwp+dE1D269OzT\n6FNx8KovUJn2Xjcgi9q0l795Gep5li77YMb8WyU7KTMZuuBfRes00xy+s7kGbY2TMpj6IQbyLwMA\nMn3WJgt99xDhL3OiAtV9pEpUkoM5DYkyJ2jiBEPrV29LSISYuvH1moZXRHu6Sa0I5T4361shCtxs\nubC4ylSAoG90OLm9wZSJov4VWGNUAF/yfTyKMaE9mi0g5BOt+Kyc9L61DilIRd97tIj2Bg9FxZ/G\nkYtK1ihQMbXDGpainHQ5Hkd8h5/tHSuqKutEB7tUMvdVJ+S3+Pkw1oHnAhfsIzmDYzdfBABUJimP\nolNG10tjZVUa3XQ8e1iFS5Ruy05zo3ENm+io3Nh87QxyeaZp+OI5ZGSOva9yDC2PDV6Fm2TBKMJs\nUr5hTx/3h9wg4qIIQkU1AYvY8E7LaB7RQLCZTthl8lx2iEVTM6FHKb9y0MTsPnWj1u/jSLTyMtuc\nr47PPZK3neFHKFe5Wc1t8V39jS/C8jJTZ84/1jBZom7sdJ+Htc1CCqUAD7875QUkbpPP2/9oAifv\n02i7W7Hiopv6rl8Tzb7PHUHfoK5raz6EXBzj1rNVPLvOFCHnVRplg7+ZgfkaDxF5r4xSmBuJubeJ\nfXGgfH6acvz6MDSSt354GWGJ9X2nLPzt2hdsCIvUrubNA0x8gWtkUy5jbo9GXuw0x9vYPoWBlZU5\nupE16HlxIKt5VLN83oEs1rHXAVW6RNnUUnjOys0xPRFHU5SKvfQc00SKhSD2wXlx2tIot3jQNZdb\nOLMrDhnRcH0iMjp9z2uvQhcNzENCD83hEFKVm7phrcMtujc5ei60vJzDgCicEHUlkFymvkjlLubj\nPEQONR1xk/Op9/ksezcIi51rTLEN0e1zo9ZdCvQy10XJQn79dglBV0y8t4aKqKlubbSw5KH+dto+\nGPrHIOSTB2/z/h3EfByP1NRhmJSFY0LsCTUVDpEfUjhUIUVoVAQ3Fbh9NEQzK9w/HTlgIyhaQtZd\nqEpMX0yoXnRL5KMArqdBzYGGwbnytyUUvFwD5VQQLjtlsSw6+DRafeyILkKXrBm8XeXnujUJNfb0\nw6lZdKGfpRFvj+tIi/KwEytC5nkDisr9qhnwo6dSfh13AzYhs7pI5wqrW8hbyZvuDMMuTrmyZYBa\nnsZa08XzYLKkod/lfPfQhBrmHr2gJLHuYtpUWBTzUfy7cFW4H1kGGuwibcqf9eCRdfQ+8jQaQ81j\nGtOYxjSmMX2C9KnweAv/LeGphV81sfeAlor39HXcnqTlutCZRilHi6vvpWd637OAiOiVGe3PwHmR\nsFTv+jnEztASKS/QarcNsnhznVbaiRMBpDyERz7fuIq9PSbWb5xk4Yjupavo1Om1nM5MYD3KyhHP\nwAc1zN/8ukmraEttYitA6Dd3OD2St+tJQmNX5TzWYrQgg9UF+HZM8b5Z9N4g/KbOiN6Thg9F0esx\ndHkV0+K3u9oBulZ6poqF47KfltE2mNQdqmqoi/6g6VADftcsfysagm/cu4mml96SEs3Bm6Z8/IXn\ngTohcavJIh/zGScU7TcBAObkeyN5W7B18OiQFjSaLKAxF3DC6NFrvokV+B2c20G7AxO0fisSrW+p\nL6GYo+cetAXRn6D1XPKU4N6gh5Nr8Dphzp1Hr0kPxmbYYG+IhtSJNGx9yq9n5Vy4BjYMnbRMFwuH\nGIqygKFoBRU7vUlvgVZuehgYyVuj7sclUUxkz8rxhituDARvj0oRnP456pTlrQ7etHGef+YuS4Te\nm28j+/uivOnrt7AozwIAapfDeHCPpTwzGmXT219COEHe8v1pJLY53wM1imSSXp+1T28gVT+AR6Hl\nH5NlDDIs+3lx4jkk5+l9pfIsonBGlOv7afLf30fFS++rPkkvIX7kxyDOMainZ2HJce15z5rYy3Ne\nQqIfckX+EVQ/i160PcAyh4C+kUXLQY93riuaUHjauNMnGhKxzcCtcd7segth0eQ806YOJV7uY/om\n31EKakg7iXp8ttfDg+foQctTXNuu//UlAGtP8Ka4JoCgSKXs0mv0HpPQ5LRhXnJDbXNsuteETyH6\noBCxh2zaMCVQrvZ0Cy7h9flNF2qi6UJCeECtbgc2G1G3drgI54Cy7Fp7MEQxnFNhXi/Vak5IHXrB\nPqWLrovPGFqjaHcph75LRVB9uldoDgLIioYVqtSD4qDcGjrh7sljHnQLRKnchoKiKAyh2K0Y9AR0\n2+P+mrebkMpcC0W9DM1CmewNinDXOIfKgPKv1noI7NGjU30AhDcaljXILo6hDl4X1soRNE2OIeuZ\nglcRhS40GwJ71qfy5nM+hj7gmmwPZxER/XIPffzumO6ExUn9lGsN9E2OZ65VwWGDOoMJ8tuuTGBG\n43mx/ziFrjhH+nIFky3yXxe9e20VCatugZA0etAEUjPMT0CZpKx1/ywAoFD3I9nnmp/0tiAVue8G\nh9cRLI1uJPM0Gnu8YxrTmMY0pjF9gvSp8Hifn2dpx43NV3B5kQEp+8hgapsBGt/3fYATOi3I4hE9\nq2fjDuBD0aM3omLPR++k9rkErnVozf/imwyO2YoEEREX7HnJA2+Hlum3sInPRvlZf5eWzlTzLuZj\nvBv7m0Ed/+48rf1HeStW90Tf3J9hUMzbX69jMsTnWp5SenCwIO4os0PY98Vl/WEM9Vnesel3gygl\n+P1AEpf8x8M45qUVXH/PxK7B32rGcRxv04JWdZa9uxXuYa/Md09mLUCOVuEw+TKWj7Ms4Ns23g8a\n1gvwuPgur67B3Bctrl55jL0B+T8jgj7eWCxAOaTnlKiMvr/e9zrgb9ALsC5wjIeWCNpdWpABVxee\nCi3iVteCoYPWvLJLL8OYOISrTvm7J9yoiFZdZl9Fz0+dsEu8O0rN2BBcE8Ftah/9eXrrHRM4qtOK\nPSHmMiVXYW9RltmMH7pAGix1FW2v8LY3aO3PLeZG8rb6zBmc/wn7bda89Cjag1mkv8ci6XJiHuYN\nytIVlxFdIyrQFwEZF7c1fG2bVvkLPTfuv0zdqbxpQhWtEgtuPtfhq2FXo65bMIvLXXonb6QamPD+\nOQAgb7L0oBGKIrrLcd0PunBG8Ky820J9SJ2pZWmVByyjrfD+cxfgarERyNqA+n3MWsNqg3EHE8HH\ncLXoPVjLQzhkvs9Ic9wO9xW4mlyn3rU+HrjpcSxEXsLxfd4VHjopf8PiwfED6qRjwobMMn8b3S7D\nVuH4XPPkoXStjoqDKEEn5EX0Jvm4bnpwrE7vY3XA5g3WWGokb1rYhLPPbc1You7IXQ1BseaDGlAU\nTQkiQx0ehwgqbHIulF4T/QDXQtypQHdQ94NVB3wD6m8pwGdZFKDrps76hgqaIc59YOiEw8l9QRpQ\nz+I9N9rgb1uyhkGUY5jNZ1HQ+O4eNMz5n7zb/ZgaviykPSIgmZldLIkAxBao/4V2HkqX85aqGUjM\nCt1wmMgUiCCFXdR/s+iHLtAJpyxjQPHCKpuwTHEvXe8QxfOG6mh7+d7iMA+baEpgaRxiVuEYnKKE\n68HwCOoMy/dG+3tI9UXDlKYCiGC5UTQsKegvUX+l1j66Te4RnXWO+935Eq6K0rCmtYVqlevpob2P\nOR/3gooI+NO0KioClWx5e8gNPm4vaeCgINAQh2jJiSakgSit2R/CZaOu2ufsaLj5DtXKcTeqRaxY\nuU5begN6g4jV4xYQGDqeytso+lQcvLu+VwEAjvdS+FfPkfHLDTdaPWJY7uUhAlVOQKNKxvv1H+O2\nj5v6ifwmtBnCjYnyHg7efx8AUPuMCEJ5t4/+Ig+R8D3Ac4mwoF1v4nFG9IhMcJFavBU83KUiS896\ncP0aN1qnx4mwaJ5+s0fFXHl5Eh89JKzyanhpJG8X+tyAyvVVTIsIya1TJdRc5DNa88JZZmCN5wyN\nitV3FWQuC6huvgr1MRXZ23Rjw8J3h1vkLVjZxqWTjGLN3TPg8JO3dmQD31Ypq88cUPFUZwHVOhWu\n6i3hKERFX35s4MDByN50nnKWZ7ewF6Ac/uD90VXQ/GoVpggqMEyOXS64YEmwWbTaD0AgeShINkzq\n3HhcE1xAzZ0WGmHKfb+mwiagPDniwEKGfDwEN2qHIaOyyHf5cg5ERW/fTKiKiKhdPKySt751gFCb\nizAlhzF1xDkuA/B2GATVO07eH4ugkZ+m1350iPQbXLzBX+KupKjr2InQMPlVyw5u+Th248NpKAqN\nmLTJeW2czWFyjYfQN1+ewAs3Bdz6pT+HuSmakk9wM3tnu4jXJBoa93M9/LGVuvq7jSaqx/ibiQoP\ng2NKHkWx0Q7XAestynLf+xZ8fs7dcIpCb36rMJK3fsoGOczgkhM6daToj+J4iLoc1mJopVkbOR5d\nQatJOXwcVV4otmEMRTTvihO/0eSBs+FOYujiBjSREO8uDP42qLC2L8E6La4mWkEcLIgepuJQqF5Q\nYAXn4/jtJsqnGLhoVAZQwbk/5qIczdcCwB8+yduky4Ku6Eo2KFMfesUBrH7OW8nqgV9kDAwrGpri\n74J+vrce1qHtzgIApHYL3S7HFgtZYEnyGZqXzzXmFHSqNNwMrxMWp+iSZW/AXRXR+CL4qFOywzJN\nOTj0LjxlXosMrXbYrOL6o3uII2l0fW0AmNsK4lGMuuirSmiFeP0gZxigWE1/Ft4FvmOqEUOvxDXQ\nkxXUgzSM5dyzAACXbRUd0fmqHJ/DwMOjQEvKwDoPsuhJGj41Yx4lk2vXeWSD3aQcrAt2ZJKUYHPI\ntev1A11Rd/ym1MOsiCx3FHPoukd3lAKAUtqEu8M9rW92UBTRw6EG97upex30RY33YdAFVeY7jnUm\nsa4SEscKg8kGR4uwd3gNEfTMwV+hMZOtlhCYpHzubfPfXBQ4dkjjyjc9jUODa69bcSK0Sz5NG/cK\necKPTIYyd1TrsK9wb7cHopAzHxsVn3kqj/93GkPNYxrTmMY0pjF9gvSp8Hj3DVoOU1eSmM3Qc3jR\nfh43W7RCTz3cxW6Pll5cWGlvHFcwFWcaw9pbdawU+Yy1ph2WaXoU3TaDqArHgaEsel4G9rCf5ueu\nMsTEkF5soMDAn4G7DN0n+kK+XUHvBUK7WisByaAl3RWBJ4fNVSRoZGFzMBqyzO/SGkt0TkESLRs9\nvfdge8SUpy3fKi7rFwEApQ9p8c2cOESkQyvr1gcGIiLN9E5pHac0egFH79EyDp/WsS3yVy+oddxb\n5jOMtTKCoLekiTD8pMuBjp2WaeZOHB4PZXrzmBPSNvl0+2jBxr7XxsMV9iX9wXNvAd95krdeeoCs\nyOG0mYSlJuy3USiS0XqxjcEUZd1xVGAIM6+T53j08AmE7eRDSfVweIoew8y+F0UPrfVzIkCsmq8j\nLIJJul4FKQc9hkHPhEP04S1lqQNDSx/VRfIeHRwholIfJFsW9QJ5DrfpJSAxGo7V974K7+8QdShn\nOQGGbxXPn2RQ0c2bDiw84tiTn+lBbjHQr2qnp7P6Q+DVK/QcPPcNeCR6mB+tTuOFDaIjhzGBWqwW\ncd1KOS0FLJjrk2eppmK4yXlZb9EbzXRMxEWXIF/0CB/VRL/T4RSUKnXNvc1xuf+hBfjak7y5TjUx\nWBWpJF5CtiVsoPWYkHIo+gIgOh3dCTQwU6Au3s7SSzgdbGBTQIwXdGDd4NrpbiXhLnLN9ezkfbdg\nxaSf20ztWQWdNfJpevvQRJqWrNO7jgQWMN8Q3WFifkhNBtaprik0O9TLQZkBLeGd0X1VOv0JSCG+\nQwtTDkGtjYpIm7J3PLDoXN82TYFD5lpudomgzPd1DCLULS3oh35ED77uH0CR6PFLbT63m/DCJxCT\nnhxGJMD/T5k+KC4q+1DkiKrxFPpNohPugQ8FkVrjNHyQRfewtD4Hh1WgAMg/wdtHShJzKY637Gzg\nqDoLAJgSwUFVWKGt03t7aLVjtkr5wqYjVuNeiRjHWMnPou2kN6k2G1gJCIh6IoFUiHOoHfLqYah0\n0NsmP1OnnLCUKb/1ow6UAL31SeHx1lIFhDqiC5nXRMXK3zaSdcTqT0+5GdqyMGXqUUbVYXssoGbx\n/LaliLRHePOpInQr105yYhfKh8aqPQAAIABJREFUOzwz7Mf43TBfwuEskYZIbhfZBMe2rMZxtM+x\nnYvQQ83ZplGycu/q9bOAlbKUWlW0De5HOZH+N9U4hDzBeXN4VtB8xHdYoknUXR/P278dfSoO3sU+\nmzv/5cEyXjvJe9m/SVbhNgkZHxlXYLwpIvBeISRnTc7BnqRAwwkJb/m4WJ7pZNH2U3jtPR6qnp4d\nmo3PTSk/B69EIZUxiWaECyd/n7CK7UUL+jkesEstCVsPX+Ygwx28MGSbtx1xd7eS90OK8x2O7exI\n3vQpHjLV3C5ycSrv8YEbR1bmGC973cjpPL09VwVscz2ENdFgO1pbRzJJ+CNkBHCg8OCwst81bOos\nDn5C5b73rBcZiTI5HQrBn+R4H+7wsOg73oHsJlzjPRaA0xTFHjobSC3z3f0AC0HYzsbxpTxl/eFd\ndSRvtfkAXNwboYXJZ7o0gFXktzldFlhFJPKyqsKsUa5VO8fr6jRgF4U7mgsS4joPQSOaRLfGxWCf\n4vwc1VxoiwT5yBDw3iG0bSxsQw/ywLHYuChsegRLFRojW+EymlsiD29gQo/SQFpTKd9YsjWSt73w\nObiT3Agaypb48hR67/Hvg5E1pM/xQK898MK4Rp4sV2YBAC/a6+jkRT7kwIWKzAV/sb6CNb+IB/gB\n53XyjIlfSpHf12MeuETa9K68iQmTev2cGFehPIXCb3I8zz0+juo8x9O6n0IqwUNaepatH1s/+dFI\n3rqlJnxhrpGHDcrca89ib57zowztOD4lrmYOglBEIZbFEHW841dxwcXP+fUZNDR+Di8bMILcrJ15\nrguvQ4Hi3gcAqEoYiVnOS+5eE6XP0pDy3eR79R9uouPhJuezAD2Re7s8KKBpFVD9DA+yTmV0Hm/U\nU0ZXHKbt4sc54l7MK9w/5JgBxSn+tmzAn+Dm2hFxAu3yEHW3uAbyyPAoTTH2LtQV8lTb4oEVLw1R\nVHigexuASPuGK2XA7qFhkDSoX24pDqeV6zxrduDL0RCDosO9JO6RTRfq66PvrgHA6eghF+I6C7k0\nKEeEf6siENo+2MZmjIZ5Qgeqdr7P7AxgxsmnrUudVfUHkKqixZ3WwoYobhFzZGGkKYuBhYdxZWhD\n1MX9URkM0R5yXmKahK4oslPwCINdtuOoTZ10RH3oN4QyDxV0A39HkYluDpawKIpT76MtcqYlQ0Rm\nN7xwdjiGodWO6hSvcay5CgriesMq9r6YWYBlj+tx2zIN2zbvYtO+NFwi1z1fJeSelWuw+Clzz6AN\nYXOh5m9h+yL3pikREq/XJ1HcYdaCy7qDBT+flXQAVehP520EjaHmMY1pTGMa05g+QfpUeLxNmef/\nCe8mMi16GacGVVjV3wAAbL6TheXZTQCAU0Ru4l4AR5O0oAbZGqYahBtu30jiboxW4fm6iGQ2Jayc\nIVwoDRsI3KfV3X1uBvV7rCwVbNKFbL6TxvMicu2DV9bh6vH/E54X8eh9en4hUUrNbzTxeEBLT3OP\nDmSZH9A7LjtLmPDS6txvngeKHHvNWoBSYXDUQZu5cFOFNGThHTeOdaEUCZvWh1uYXCQEuCaCGmRP\nB60F/n3M8giXRIm6rPsQ/ln6SZHjDFI7sCxj4YAW+n1fDPYg80m/by7AWdoHAFRnaDVeeqyjLQxU\n7bQb+PqTvM1tPsRGUHiFu6JxdXAS8Rat1ajRQWpKREBW+/AIyNI/SRjSESthT/SDjug2BKz0EMuy\nCXWO7sP+PuUXcjWQcdNTqetZKOdo/cpSBAOBGFRE4JRL7eJApXyCqQjkBOdroFoQS/K5vi7/Rl8c\nncerNLLwispUdie9pXfNh6i7+Y7fmpjEj/+C49lcsePCRc6XU6Z1rNR2UH+Vntfp3gu49zqfUTjR\nw6KHnth+nznZ5fw+Xndx7puFLJoz9IYOPozgC+fp2X8o0yvadKzjzHXq+o+kMgJD6sMZtQ/rUECA\nN/+az9dHR8ietzpwTeRozp8kKlJLz+KSgEKX1QDK9/cBAA/m5zEVZARzfEhvtrfdxr6byMtC3IC7\nRhTlUa8Mt5PezrKd82OtnodPRME2h2uo2yjTicUYQvfpMVhmKbNMyYrcqVnK7Md7MK5Sfpn7U7Av\nEcp3i+bkuedHozB9zQe/g56/vUxvy2VYUHZyDJFCBZ065SdPOtAWHo5p4VgCdg1RgYjaywradq7Z\ntqULRWQMBOvcH9onc4gdcV4ln4S2zrXncobREFGuU3buC8VuCUpDlIn0Kejo9MIyNQOTNVF9rCvB\npk4KTh49yVy5DZ9MuTaKs7A7GehzWCJyNRkuIs6pQsXihTnJ7b1rdgErdbV2i+/VJ0KwxIQnVxnA\nVLgu7nRNTFvovTVEQJql3wH89PbbAyeKkyKSu2mBT6Iu98tiHQV68MSJosh6G9ocn9Wva9D0p0c1\n17pRdDL0pD29CnQRId7OkrfYsIduiLrTrOVgZETzesMDtcOxaSbnvRp0o5/k3J/rlpAKcm0edjR4\nvPx+18FrleWaB7akyNt2ReB2kZ+m4UTsDhGZjkA1LG4VkkIkyNm2IucXyN5BGBH1/53H+6k4eIv7\nZGDJpsP8kILJxKeh7HGCG84UbEKhrLNk8K8WY/inXkauvVlOoevnpF10zsA9xb9ThxT48o0hKn0q\nVlF5F29JjKL27q4hHmUCfDlKUfyKy4oDlfipy1pFOk9oxv3DJoIuLl7bacKflT03QuIqJqDYRvJ2\ndEMkrM9GMJ0nPDI8cCMt6qiejXrxcIEHY0CUGMT0Au7ZOOmn9ElIx7lJDh970RRIlLcmEr2lZZwS\n5SXL2Ti+PsEBXdF+BtUSN0FrjUaFo3kT3/ByV/lFpY57SSrU5KwDlw5ZFvCDLsdY9CRg16j8z9lz\n+NcjeHscm0Nsh+8o+7ig0bEjI+rC1rUqpgWUqyckFII8RHyilOWevIJFGz87HG6YQW5sk8k4Urq4\nR2uJ+rYBNyZ1WgLt9iJcJ3nnmT/KY1LmcxUf/98rW2AtUJZHagANH++AlyQF+wkuUmeHMo1UR6dK\nbc0dwn5EWW6C8NJstwVZ3L1Xv7uLyxf4eXK6jHVxB3m+zrnwWWeg/GvCx0dn30JwmmM7TC1gY0j9\nmu9w3mdPv4ZtUes2upOH1BL1eD8fx3e2eN8WG9C4msEetsUdWr/yDp6ZeIlzUevg7TzvfpdmeCid\ncpXx7RG8GUoCkRDlk0zyIJvz5RAT6vdh0YdZLw+AM/vfxcMFXj/URHnV+fk2LAOulyNvGd77lO+F\nYxb0O6xEUVvcBwAEqzWse3iAXjC6eJznfJ+ercLT4nhLoqSp97kclAO+txkMofsR5yi6aEPIzTvK\n1EmuPW1r9Lz15BAyAlq0Rvle2duBuNGA6nLBWefYfeU21qNcZ/40f1CckGBUOK8uWxumiN52OG1o\nNvjuVpj7S6WjwePmviM3mohJNOZKqgdBUfAkK1LR5GYM1ikB1dcGcAqDVdGqqA5FjedhGS3H09NS\n/BEbdLHPGEYHhpfZDiGQBzs8GJocg0X34rBBnfRYJWgS16Fxljrty05gyyqK08SPwdvlOC3tPOxi\nbLIhHIwJH9rFfQBA0COjZKd+SUc6ZAfnsOfnoTqhzaMpysBqmgudI44tH7TDKtIMR5Em12ATqXir\ngxaONanv034W4Cge9oAS+W1NOhEucf/LlgpwBMQ98iOum62AF+GoiGJXDXQPOUeBZw6hNLj+V3YJ\ns8uqibqP8xqK6WgsEKrH3TJQ5nik2McHexeJltiXBk24QYNp07uBU+boYjVPozHUPKYxjWlMYxrT\nJ0ifCo9XT9OdLc8twp+h5ZlPNHAiKGrRnT0H4zFd/FtFemb/ZOo2Nksc/s7qL+DCIuHjTugBmiat\nlrMihzZzYQgYIgcvdxq6gMmw0UBrjhBJfIGW1Te6Qbin9gEA3mQc572EAB9d0uEL8bnH+gz60h5P\n4gef5TsuFA5G8uY4QUuzlg2j+QyhOiW0jJcO+I7DIPDsJi2nuki6D+svwiYaJ5S2t7D4eb73bvUe\nHqq0vnxtWnzB4EOsBhgoIKtJ/MIevcaSJGPtvCiZd5terJKYwpcEfLT3KIjlEL9vHNax9RIt1wka\n6ujdzWF1iRZk9/ujgyIW5EO0pojVzQ85hoJ7DRFDQMrNPrrC0xh2l2Bv0YPpzxD2mq6sIS4gubTW\nQatPO9AaGyK4T2u9uEioyR1LopQUnUXC++hv8HuXu47GgDKWK7TEG40DyAPCtXXLIWZbIo9vswP7\nAufbolLW3eFo29PzAwVzi9S12wd/xvHavoJ+gNbxZuB5YJv+ZHRVwsUrLHCR7nPeyqG/D/Xs3wAA\nDgeTmOhS7s4TDcREl59AiEVQHLlvYOeQyEpMd2BX5Fcfu3sXB5+h91Eyqf+BGxWkswyuuuicwbUI\nA+By+TrmKxxv307PajP9cZbq/5Oy/SpsGxzP7BLlYHOEkZ4h/Dbz8BH0XSIZndg5uMXzpg84V1s2\nCaqPcrMXD9H+HL18x6ofthDzRXM90Vms3YZq4d9fs0TQFbB9dc2LIxHYFBaRzpZWCKEFrqe8xUBb\n5prORPdge0xYXjrO/49c0AC89QRvlbIGT5wy6/REF6KmjIHEd9UCQfhB3o5UN4KiU5QKet3dSg+G\nTUTMd2IIiuIz/a4fPhvRq1xflBDtzaCS4BiNThRmhMreqxsYVMiTuy72pcE26q1ZAMDQ2oUpCpQM\nen30NCJpirYCn/T0Aho1zQVPVQT8WPyoH1Enyhq/m2xOYUNcu/Q9W3C3uW8s2BdRPiDSUHfQaxz6\nK7C5eYVVNcIo90SQY7+GvkwPsSkitu3dNvoK99pmwIr+Ifm3LFghi8DFuS55qETbEA44bFsD+M5z\nPJmCFzvy00tGOqQqenbuC6e7BmqyCHoV2SiDZ8IwRFGNetqAJ8A1oDai6IuMAHmO3ui8rY9BmvO5\nKw3hneYYOzfm0Qtzj+jp3OiidicCfiJT1bwbIR+h/LjLhkMn9dYnvGSne4CSxH2y2y3CKwLHvGYZ\nVUSfytsoGnu8YxrTmMY0pjF9gvSp8Hhd0hcBALdv38Wzx3gHOT3IopMTBbg3/WgE6VEuBtnA4G5l\nCpYBrbiFmWuw12i5v2cC5016EqEaAzJSw13cifNO6LJFxdScqJA09RXUHtND2VZEW0HpHXS26b1k\nFAPObd69uRsn4VdoJX2U4P2DmujjF2y0tlbtZwC8/gRviT49C1v726hWWO7OzObQEXfSKH0IvS9K\nnhkMDoBvC7ZdBoO5pyTcXqN3lwh7ESjRUt4MigAm+DH9UARDnIzCMkNPw3bzFnw53pe5RbCZ+aCH\n/kv0BuInj5DOiFxMLYyPRHH6Z0Q1oZLNxIUuZbb/c7PA20+whmrLBZeNZQRbWXH5rGhQS3zuB0En\nAhWOTetVMRT5nF19FgAQnlHxWKRE2G0eyA3eARkVQBbNDGzi3iy9eRw+jXdHps2PKVEsP90MA37e\n8Vo3qRs9xxwCWT63vbIAc5eWa32iB1ebtmazSPlZI94nGQNgWVbxgzz1L7799wEA67+9AfUjUZ0o\nkEaw/h/zWbX/Cb5HojxfhalbxYWv41yTss6fOYOQl17WwbduoPcrvAfN32ZKWfNoBsErIkUlVYLP\nzTvTt6K/g/n9fwMAOBIlTZuDIHxnKRtVCkNfZ+lHV9UBq5MxD1E7A672OqPvQZ0WA8VXaKFX1uhd\ne9s57O3RY4jJDWSWvwQAONG5j4BIldrz8R5v3p5AscZ5Dw0j2K3Qs8617YjqRK+kGsdQm9LhTO8D\nAGRYEYqK9DtrFfZVzqc7xO+S1j1cDXItlJQkJkxRFvTgHJLP0JN2PSDvT8ubtCsVuFSukWaXumdF\nE4Ys4g4aZfQM0ZSkUYNb9IYeimAnoxiGJyL6zVqBkiZaVZpdtMF1JAnPV2mkYc9zv+oFHZBFfnrL\nUkd/yO+TomerS1lBRTSDcM950azytxO+IQZtkXITTGFY9YzkCwDS3QHMAb3xlhewin1D73PvSkkN\nmKL5xUKiDalCPdrotqFKRK16baJ9fp8DhmhSoXRUDNz0eCPWBqZFP/O+R1Rh2zDQmhPVy/IaHBr3\nLltOAmyU2yMP/961aEX7Onn2uweoidzvuL2Aul58Km812Q/pEfVh4HcjKkqOVkWOvlZIYUs0fbA2\n7chp9I5b3QZsk3zfQOQt23Nz2BElfCc1HSXRrnEpHESlxt8qYp8st/yYzHCdFD0bSIkUq5jzEdQS\ng+gKPQYghnQn1KYIonXJ6IjGE/ayG61W9am8jaJPxcGb7lAwl+FHxtgHANhvn4Jtgov4cSSJSzkq\nZLTPiW4eVOFVGRjVaBeBOQpnsXcOxoDCvZ//uGxbAF8S9W/ljAa3n8qZy92H/SI3xJUD/itlzsJq\nobIU3B2YHZHzZ9xG3c2FE1gXBRX0R6i3eRgvBUcXYripcgHGXV/AsMV3nE7s4Ufz/D73wat4wcOJ\nVwQc5jILeHyZUdy2vfMIn2fv0/LmSRg2HhxX41ScHckC15woClG1Y2ARh9AX99G+zt/G/x6VsGGf\nRFs02u6vDWEXgUt7V11YdBCCbXe4QM8tNvDAJNyT2B6dMzloSNhx8cB1OykbqT0Dy5Df9bptmAo3\nYGukAEeNUHsmQIjMku9joiFyOJUeknEePrayC5MiJ1LU10D4vIRKmr/V9ANsF/mOFYsDa4ciCOcU\ndUTZzaK8TJmGM330Spx7p+RGRaNx41SFEVAdHdXs2DWRSPGgeeMs9eiXcyewofJwiw9PoP38HwEA\nmv2fh7zJ7k5lOxfuGW0aR9PcJCe++wClsxyvX55BOEc+k9z/sX92El8WubJ64HtYvcVD7aUzWdRW\nuTk+c5z6Umk40BURlLfbj/BqiUbg45eDePk2c9Vff8B5mxQdY36aKp4UerfZJ3laYmWUun8OIY0b\nedwlw1FhxHsv5UJqgQdDXED5zfIm1qyE5FqWY/AkCWl6k9vwvSiijQu8jvGnTuOu6Ly0tFXHodiI\na/E23DPU9xtV8hiPzOHrP6DBFLCdQHyRa6tSymFJ7HfZS4QFLd30SN4SLh8OTf5YE0ExIcNEsSQO\nhsk2pArnRZEkFPe5uUanRYBTpIKszvmxIwBV1H3O6W5IoquRQ+Q4N7sWlEUfZk23QBebvVqpoGgT\nhXfqVOA+7GhkufgUlw2Kj+/Tg33Yt7iWtUIPXf/oEqYAMFFsYCDNAgDmN5PIOyirSIId1hxOG+Q2\ni5EoB7PIhakznsEmumHykRBFLFS7CU+fY08cDtAXXap89YsY9umYNMSVkcNtgZoSV2bxEgZV8lSf\nX4Jvkzyd6lGmzfV1GMdFBkkhi6zoq20ZOtGqjw5ABYDi9i34psQcOExkt/YBAO45EVndm0NC9N02\nrBYMO9zjW043vBsiaCvK8ea9eUyZvJaq6MAp0ckoKfdhPcmx55qUo696gHaI+m1o83AadMQKKQlt\nB529aQ8dn2JmC21Rmz/ebKCV4zv2bQ34faMLujyNxlDzmMY0pjGNaUyfIH0qPN7bCpNED+bmcI7I\nDn4y9TaeP6J1G3o0QP3fYSBQ+Ye0nt1aH9++T4v5y7EujO8waCD5uQEmZXqL187QC72yuYVG4bcA\nALMuA9cs/zMAoNE6j3Nv0vutvsAXL5Y7KOt8R2ViE4vvMpUkdjmGrym0gE43acXNPdtD+m16OJ7o\nk4EeAGB7QOtR8jdQLhJ6fD0IHLtLiy0wsQu1z6CY8D49LGPajt8U5Q9TMxnc6BKijhfccL5I6y28\nyqkLTOaRdNFTSQ4UTFboJXQHxxA6xd9MPuT/r/Z2cLouAm7CYWgXCe3sNIZYtlFmWpjv/XDXiweg\nhb/gGQ1ZWjIWeAV0lZ+nJbgs78Lnooc50T2OcEnkxdlN9DxEJVbW6WX0ImFUE/TebJU8pgpi8qMd\nHIk+vW4Rpt/bGCDgoWVq6fugt6kbe84t+OYEhFekTKu6DeoR+aw5+lCP0VIuZxUYKnWmMaD3rMZG\nF6Xf20oi4yFs/EKaHl1ttYbY5xmQ8vYbu4gNmCfd7rXRdfB5YZF3mLdncOs9ellnp3ZReId8TP9s\nFj/OfIzecNwvrn0HGy/8KgDAWdWgVenJvL3qwWCWAYbSfepIzLGIIz95Wzko4a9DhK0Df5XHDxep\ni5YqkaKsFBrJm2a7iPx5ellVmeVKw8VVdE1CiB91M9B1BoCFl6qo7xFG67lo1c/WpzEzID/BymPk\nZwTU95Id5feJIAwSlPlacojpSXpkq5of1iBh/ylTR/YGZek8Qx042m7CEPnk9S9k8b+LcpgvfWaA\nnW3yGX1EvUj5wiN5q2gd2Gz0PM0C9TajAkWda9d2GEbEoPy7E00oy/Qwa6LCWtM0gSbnu9grw3KS\nMnSkatCm6MU2GtR1U9bQOeK+tGC4kYpRP0uqBIvOdV/XCI+6G324T/H/ax0bogJe3m1GoLU5zrzb\nDXdpdH4yAPS7GWgH9Cy3/cuwxcQ6U7hvfGQ48cUO19C9yR7ONOkt7pYWkPi4qlaEsrZ3o7ibEI0P\nXCryokuYbd6Frl/0JhfBqz67BekyP7fLPiyLRiDqehUtBx/8WARnLSoqGre45ldtfbhF96eOV4Ol\n83d08HHNoiC86kFsgJabOqWLvs6yfQO2I+5jvYUhpCGvSqImYOSoU445EayX8iEgqoSF8074Ehz7\nQrOHkugJ7tK5hoxlJ5Cn/xntleEXKVrp1D7CLgF3uziGWHiAepprZJh5gKaocCYfuJHyjUZgnkaf\nioNXsXFCuutncGvmXwEAXt56DZnTLHnXDZ2C71/yAAydIGSXsCRRPyMKBihdnFjk5/P2Rdw3qJCn\nRH7w5ufnEd3nfe+aGcQL1a8AAO57b8GxSMWoFrnYMn4dGzH+3a99cA4fXeBBV/DWkfCLzejgfwMA\nXNvwoHKR0ER/Y3TnjTtThIlPWlcga0IxjnRIXSrOclSH38XI1KaNMHE0U8E7Lm40Vm8AviyhLfXF\nGqIZbji7js8BAC4WvZDrhNaGs7vw2RhdvNN7hDmTm2ApxAPv51eP4V+6GYl7dfEKTHEnFTmUcHhK\ntEXbJcQYVmWc6lE9vMnMSN7MxRZKogDzySPR2szZQdcUi6V4HcMgD0hnKA5/l0qbN0S0dScPd4fG\nkRa2YF+0flOzPkBE21bSovBBexXWNmFrdToLQ5Ty6x/FIfso16Romehw96DkqVOeag1D0U1mztZF\nXnRnsg3E/VZ7dMS27VUrpg44L4+alP/VwHHcqnBezi/mEXaLBuZ1K/QB+c+Dz4vcGOKVV6hTZqkN\n/TJl6HgwgeC0MHKC1LNUKYHp7/4EABCyHuLmFKE6fzeNc4VLAAB9SDnmmm1IKuU3E5DR2/uvKOul\n34HnkIfAjUOOa8IxOtJyv6AgVCBk3pb2AQB7/lPomd8EAASrMzhsUw8KySk4TMpyL83NrBCToXV5\neO0+48NkgQaELS+j0+FmVDRplEwv7EH7EeeyF95AS+QCO6pXsHXxOgCglKLRcuW4impEQIHbi/ic\nn0ZkYfMA9hleU2RDPAiDh6N5sw0syDUJPTq6IkakAzR0fjf0ldAv8nDqSSo6Hc6LRdw4+GNeqDXq\nnBF2ATVeDw10GZYO9wpFFKmpS1XIAY59d5hCEzS6VFOCrUFdV0WFjj0/4MlQfrLkxJ5GXdcqbjiC\nhGvnjTbsk0/Pde23HPAviIIe/hy6+9yP+jY+62pziOvHyLN3vYvWAmXmmbXBIYpLBLuEl6VQFc83\nOYf6QEJ8lnOsSUWEGjTgkl6REyy7MGPhGJ2dPnI9zotraIMm04BwdqnrkzagskDHRN6roaZw//Q/\n7KGidp/Km0dqwxEUsQKdJXhFKd9Aj3LUHUFYwtQjZ9WDZp9y8Nk1GKJ1a0fU659RjtAWEdDDhQiy\nYt5sYScsSdEWNUD9cfSH8Nk5rgM1Dl3U7LbMuxEVRpDDRn2IZgFJ1CAY+ifQbIkiMVEbFvtPj9g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rI/+BhBCWZPEbjAfeHI1UVc+j0bC0N0T+kVL4aZS6D23fA7pcmEpYvOjkSuvB247NLS8SE9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losZFroVmpAxznH/XWlpARPOnzv0A3+5+CQDwVYU6FFSXUTrD0oTlWA6Ht8jPfN8JNW+P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\nVwJLzv95AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd246f03d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cs231n.vis_utils import visualize_grid\n",
    "\n",
    "# Visualize the weights of the network\n",
    "\n",
    "def show_net_weights(net):\n",
    "    W1 = net.params['W1']\n",
    "    W1 = W1.reshape(32, 32, 3, -1).transpose(3, 0, 1, 2)\n",
    "    plt.imshow(visualize_grid(W1, padding=3).astype('uint8'))\n",
    "    plt.gca().axis('off')\n",
    "    plt.show()\n",
    "\n",
    "show_net_weights(net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tune your hyperparameters\n",
    "\n",
    "**What's wrong?**. Looking at the visualizations above, we see that the loss is decreasing more or less linearly, which seems to suggest that the learning rate may be too low. Moreover, there is no gap between the training and validation accuracy, suggesting that the model we used has low capacity, and that we should increase its size. On the other hand, with a very large model we would expect to see more overfitting, which would manifest itself as a very large gap between the training and validation accuracy.\n",
    "\n",
    "**Tuning**. Tuning the hyperparameters and developing intuition for how they affect the final performance is a large part of using Neural Networks, so we want you to get a lot of practice. Below, you should experiment with different values of the various hyperparameters, including hidden layer size, learning rate, numer of training epochs, and regularization strength. You might also consider tuning the learning rate decay, but you should be able to get good performance using the default value.\n",
    "\n",
    "**Approximate results**. You should be aim to achieve a classification accuracy of greater than 48% on the validation set. Our best network gets over 52% on the validation set.\n",
    "\n",
    "**Experiment**: You goal in this exercise is to get as good of a result on CIFAR-10 as you can, with a fully-connected Neural Network. For every 1% above 52% on the Test set we will award you with one extra bonus point. Feel free implement your own techniques (e.g. PCA to reduce dimensionality, or adding dropout, or adding features to the solver, etc.)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "best_net = None # store the best model into this \n",
    "\n",
    "#################################################################################\n",
    "# TODO: Tune hyperparameters using the validation set. Store your best trained  #\n",
    "# model in best_net.                                                            #\n",
    "#                                                                               #\n",
    "# To help debug your network, it may help to use visualizations similar to the  #\n",
    "# ones we used above; these visualizations will have significant qualitative    #\n",
    "# differences from the ones we saw above for the poorly tuned network.          #\n",
    "#                                                                               #\n",
    "# Tweaking hyperparameters by hand can be fun, but you might find it useful to  #\n",
    "# write code to sweep through possible combinations of hyperparameters          #\n",
    "# automatically like we did on the previous exercises.                          #\n",
    "#################################################################################\n",
    "pass\n",
    "#################################################################################\n",
    "#                               END OF YOUR CODE                                #\n",
    "#################################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# visualize the weights of the best network\n",
    "show_net_weights(best_net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run on the test set\n",
    "When you are done experimenting, you should evaluate your final trained network on the test set; you should get above 48%.\n",
    "\n",
    "**We will give you extra bonus point for every 1% of accuracy above 52%.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_acc = (best_net.predict(X_test) == y_test).mean()\n",
    "print('Test accuracy: ', test_acc)"
   ]
  }
 ],
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